2359 Monetization Jobs - Page 45

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

About us : We are a Full Lifecycle Media Network with over 27 owned and invested ventures in creator economy, social commerce, media and technology solutions. One Digital Entertainment : We are Asia's largest network certified creator and digital video network with an unbeaten repertoire of thousands of creators including some of the biggest global youtubers, musicians, artists, brands and publishers, clocking over 3 Bn+ views per month through a network fan base of a whopping 1.6 Bn+ . We are known to cater to our talent’s every single need, from planning and strategizing content to production, syndication, distribution and monetization of the same. Title: Influencer Marketing - Campaign and Account Management (Min 5+ years exp) Designation- Manager or senior manager Location - Mumbai Job Summary- This role will be responsible for end-to-end influencer and client account management. The key responsibilities will be to recommend the right set of influencers, negotiations, timeline alignment, and coordination with the in-house production team, brand, sales, and creative team to ensure alignment with campaign goals. To create campaign reports, manage influencer payments/due dates, ensuring delivery of assets, incorporation of feedback, problem solving and relationship management. Roles & Responsibilities : 1. Strategy Development & Campaign Execution - Design and implement influencer marketing strategies tailored to brand objectives and target audiences. - Develop creative campaign concepts that resonate with audiences and align with current trends. 2. Influencer Identification & Relationship Building - Source and establish relationships with key influencers, Key Opinion Leaders (KOLs), and relevant personalities to leverage their reach and impact. - Cultivate a strong network of influencers, ensuring alignment with brand values and campaign goals. - Maintain strong relationships with partner agencies, brands, talent management agencies and obtain the best possible costs that are largely better than our competitors. 3. Content Ideation & Curation - Collaborate with the creative team to help them with influencers to brainstorm content ideas that are engaging, on-brand, and optimized for various platforms. - Curate a list of influencers that aligns with the brand and influencer’s style while meeting the brand’s messaging and aesthetic guidelines. 4. Campaign and Account Management (Vital for the role) - Oversee end-to-end influencer marketing campaigns, managing all stages from planning and activation to execution and reporting. - Coordinate with the in-house production team, brand, sales, and creative team to ensure alignment with campaign goals. 5. Budget Management - Plan and monitor campaign budgets, optimizing costs and ensuring campaigns remain profitable. - Track expenses and revenue to maintain budget integrity and meet financial objectives. 6. Finance & Billing - Work closely and deal with finance and billing processes, ensuring that influencer invoicing is accurate and talent payments are executed within due time. - Manage payment schedules, reconciling budgets, and keeping detailed records of financial transactions. 7. Industry & Trend Analysis - Conduct research on industry experts, competitors, and target audiences to stay informed and adapt strategies to market trends. - Stay updated on emerging technologies, trends, and the influencer landscape to proactively adjust campaigns. 8. Relationship Building with Stakeholders - Build and nurture strong relationships with influencers, talent agencies, and internal teams across departments. - Ensure all parties involved are aligned and satisfied, from talent to clients and internal collaborators. 9. Campaign Performance & Optimization - Track and analyse key performance metrics to evaluate the success of campaigns, providing data driven insights for improvement. Create a detailed report and send to the client once the campaign is complete. - Use analytics to refine strategies and enhance influencer partnerships, ensuring future campaign success. This role requires a creative and analytical mind-set, a strong understanding of social media platforms, and a proactive approach to building and managing relationships with influencers. The candidate should possess excellent organizational and negotiation skills, attention to detail, and the ability to work within budget and time constraints while maximizing campaign impact. Industry

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Company Description Unibots is a Next Generation Ad-Tech company on a mission to build innovative monetization solutions for publishers worldwide. We focus on creating state-of-the-art technologies to enhance advertising effectiveness and revenue. Our goal is to empower publishers with cutting-edge tools and strategies to maximize their monetization potential. Role Description This is a full-time, on-site role for a Unity Developer based in Delhi, India. The Unity Developer will be responsible for developing and optimizing mobile games, creating immersive augmented reality (AR) experiences, and designing engaging game levels. Additional responsibilities include utilizing object-oriented programming (OOP) principles and other programming techniques to ensure high performance and functionality. Qualifications Proficiency in Mobile Game Development and Augmented Reality (AR) Strong skills in Level Design to create engaging and dynamic gaming experiences Solid understanding of Object-Oriented Programming (OOP) and general Programming skills Excellent problem-solving and analytical abilities Ability to work collaboratively in a team-oriented environment Previous experience in the ad-tech or game development industry is a plus Bachelor’s degree in Computer Science, Game Development, or related field

Mavenir is building the future of networks and pioneering advanced technology, focusing on the vision of a single, software-based automated network that runs on any cloud. As the industry's only end-to-end, cloud-native network software provider, Mavenir is transforming the way the world connects, accelerating software network transformation for 250+ Communications Service Providers in over 120 countries, which serve more than 50% of the world’s subscribers. Role Summary What will you do Applied data science research to fight spam, scam and fraud attacks in SMS, MMS, e-mail and other mobile telecommunication protocols Helping mobile network operators worldwide in localization, identification, monetization and prevention of spam and fraud attacks Big Data analysis of Voice/SMS/MMS traffic (>100 million messages per day) Data cleaning and preprocessing (data wrangling), exploratory analysis, statistical analysis Machine learning, data mining, text mining in different languages Data visualization and presentation Uncovering activities of organized groups of spammers and fraudsters Researching new fraud techniques and designing algorithms for their detection and prevention Monitoring and preventing virus and malware distribution vectors in SMS/MMS Presenting results to customers, leading discussions about findings and best approaches to manage the fraud attacks . Key Responsibilities Key Responsibilities What will you work with Hands-on Experience of 2-4 Years in Statistical tools – R-studio, python Mavenir’s solution for identification of fraud and spam in mobile networks Unique data sets (Voice/SMS/MMS/RCS communication from all around the world) State of the art fraud detection algorithms Core mobile network systems and technologies Must have hands on expreience in Linux/Unix OS(Mandatory) Big data tools - Spark, ElasticSearch/OpenSearch, Kafka Data science and machine learning tooling - NumPy, SciPy, MLlib Job Requirements What we expect you already have Practical experience with statistical analysis or Business Intelligence Scripting languages (for example R, bash, python, perl, lua or similar) Data visualization and reporting Critical thinking and strong problem-solving skills Curiosity and willingness to learn new things Working proficiency in English We appreciate you already /have - Machine learning and Linux This position is based out from Gurugram location Accessibility Mavenir is committed to working with and providing reasonable accommodation to individuals with physical and mental disabilities. If you require any assistance, please state in your application or contact your recruiter. Mavenir is an Equal Employment Opportunity (EEO) employer and welcomes qualified applicants from around the world, regardless of their ethnicity, gender, religion, nationality, age, disability, or other legally protected status.