629 Xgboost Jobs - Page 6

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!

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!

Programming Languages: Python, Scala Machine Learning frameworks: Scikit Learn, Xgboost, Tensorflow, Keras, PyTorch, Spacy, Gensim, Stanford NLP, NLTK, Open CV, Spark MLlib, . Machine Learning Algorithms experience good to have Scheduling experience: Airflow Big Data/ Streaming/ Queues: Apache Spark, Apache Nifi, Apache Kafka, RabbitMQ any one of them Databases: MySQL, Mongo/Redis/Dynamo DB, Hive Source Control: GIT Cloud: AWS Build and Deployment: Jenkins, Docker, Docker Swarm, Kubernetes. BI tool: Quicksight(preferred) else any BI tool (Must have)

Designation: Lead Data Scientist We are seeking a highly motivated and experienced Lead Data Scientist to join our growing team. In this role, you will be responsible for leading complex data science projects, mentoring junior data scientists, and driving the development of innovative solutions that leverage data to achieve business objectives. You will apply your deep expertise in machine learning, statistical modeling, and data analysis to extract actionable insights and drive strategic decision-making. Experience: 8–11 Years Job Type: Full-time Responsibilities: End-to-end delivery ownership of ML and GenAI use cases. Architect RAG pipelines and build enterprise-scale GenAI accelerators. Collaborate with architects and presales teams. Ensure code modularity, testability, and governance. Required Skills: LangChain, LangGraph, embedding techniques, prompt engineering. Classical ML: XGBoost, Random Forest, time-series forecasting. Knowledge of Python ML stack and FastAPI. Strong understanding of security and cloud optimization.

PwC AC is hiring for Data scientist Apply and get a chance to work with one of the Big4 companies #PwC AC. Job Tit le : Data scientist Years of Experienc e: 3-7 years Shift Timin gs: 11AM-8PM Qualificati on: Graduate and above(Full time) About PwC CTIO – AI Engineering PwC’s Commercial Technology and Innovation Office (CTIO) is at the forefront of emerging technology, focused on building transformative AI-powered products and driving enterprise innovation. The AI Engineering team within CTIO is dedicated to researching, developing, and operationalizing cutting-edge technologies such as Generative AI, Large Language Models (LLMs), AI Agents, and more. Our mission is to continuously explore what's next—enabling business transformation through scalable AI/ML solutions while remaining grounded in research, experimentation, and engineering excellence. Role Overview We are seeking a Senior Associate – Data Science/ML/DL/GenAI to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team’s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation. Key Responsibilities Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases. Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments. Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes. Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs. Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives. Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions. Conduct R&D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics. Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team’s work. Required Skills & Experience 3 to 7 years of experience in Data Science/ML/AI roles. Bachelor’s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA). Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc. Hands-on experience with Generative AI , including prompt engineering, LLM fine-tuning, and deployment. Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows. Strong knowledge of NLP techniques, transformer architectures, and text analysis. Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered). Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch) Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc. Exposure to deploying AI models via APIs and integration into larger data ecosystems. Strong understanding of model operationalization and lifecycle management. Good to Have Experience with Docker, Kubernetes, and containerized deployments for ML workloads. Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.). Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js). Demonstrated track record of delivering AI-driven solutions as part of large-scale systems. Soft Skills & Team Expectations Strong written and verbal communication; able to explain complex models to business stakeholders. Ability to independently document work, manage requirements, and self-drive technical discovery. Desire to innovate, improve, and automate existing processes and solutions. Active contributor to team knowledge sharing, technical forums, and innovation drives. Strong interpersonal skills to build relationships across cross-functional teams. A mindset of continuous learning and technical curiosity. Preferred Certifications (at least two are preferred) Certifications in Machine Learning, Deep Learning, or Natural Language Processing. Python programming certifications (e.g., PCEP/PCAP). Cloud certifications (Azure/AWS/GCP) such as Azure AI Engineer, AWS ML Specialty, etc. Why Join PwC CTIO? Be part of a mission-driven AI innovation team tackling industry-wide transformation challenges. Gain exposure to bleeding-edge GenAI research, rapid prototyping, and product development. Contribute to a diverse portfolio of AI solutions spanning pharma, finance, and core business domains. Operate in a startup-like environment within the safety and structure of a global enterprise. Accelerate your career as a deep tech leader in an AI-first future.

Introduction IBM Infrastructure division builds Servers, Storage, Systems and Cloud Software which are the building blocks for next-generation IT infrastructure of enterprise customers and data centers. IBM Servers provide best-in-class reliability, scalability, performance, and end-to-end security to handle mission-critical workloads and provide seamless extension to hybrid multicloud environments. India Systems Development Lab (ISDL) is part of word-wide IBM Infrastructure division. Established in 1996, the ISDL Lab is headquartered in Bengaluru, with presence in Pune and Hyderabad as well. ISDL teams work across the IBM Systems stack including Processor development (Power and IBM Z), ASCIs, Firmware, Operating Systems, Systems Software, Storage Software, Cloud Software, Performance & Security Engineering, System Test etc. The lab also focuses on innovations, thanks to the creative energies of the teams. The lab has contributed over 400+ patents in cutting edge technologies and inventions so far. ISDL teams also ushered in new development models such as Agile, Design Thinking and DevOps. Your Role And Responsibilities As a Software Engineer at IBM India Systems Development Lab (IBM ISDL), you will get an opportunity to work on all the phases of product development (Design/Development, Test and Support) across core Systems technologies including Operating Systems, Firmware, Systems Software, Storage Software & Cloud Software. As a Software Developer At ISDL: You will be focused on development of IBM Systems products interfacing with development & product management teams and end users, cutting across geos. You would analyze product requirements, determine the best course of design, implement/code the solution and test across the entire product development life cycle. One could also work on Validation and Support of IBM Systems products. You get to work with a vibrant, culture driven and technically accomplished teams working to create world-class products and deployment environments, delivering an industry leading user experience for our customers. You will be valued for your contributions in a growing organization with broader opportunities. At ISDL, work is more than a job - it's a calling: To build. To design. To code. To invent. To collaborate. To think along with clients. To make new products/markets. Not just to do something better, but to attempt things you've never thought was possible. Are you ready to lead in this new era of technology and solve some of the most challenging problems in Systems Software technologies? If so, let’s talk. Required Technical And Professional Expertise Systems and Cloud Software Engineer: As a Software Engineer with IBM Systems and Cloud Software teams, you will get the opportunity to get involved in all the phases of software development and work with technically accomplished teams. The responsibilities comprise of design new enhancements, coding (including test automation), problem determination and bug fixing, performance analysis, and solving client problems. You could also work on IBM Compute and Storage Systems including Virtualisation, I/O and Reliability Availability & Serviceability thereby, enabling the creation of a seamless software user experience across the stack delivering to IBM’s Hybrid Cloud and AI clients. As an engineer you will be responsible for enhancing and maintaining the key components of the Software stack, Platform enablement and an opportunity to work on closed and Open source development communities. Required Technical Expertise: Knowledge of Operating Systems, OpenStack, Kubernetes, Container technologies, Cloud concepts, Security, Virtualization Management, REST API, DevOps (Continuous Integration) and Microservice Architecture. Strong programming skills in C, C++, Go Lang, Python, Ansible, Shell Scripting. Comfortable in working with Github and leveraging Open source tools. AI Software Engineer: As a Software Engineer with IBM AI on Z Solutions teams, you will get the opportunity to get involved in delivering best-in class Enterprise AI Solutions on IBM Z and support IBM Customers while adopting AI technologies / Solutions into their businesses by building ethical, secure, trustworthy and sustainable AI solutions on IBM Z. You will be part of end to end solutions working along with technically accomplished teams. You will be working as a Full stack developer starting from understanding client challenges to providing solutions using AI. Required Technical Expertise: Knowledge of AI/ML/DL, Jupyter Notebooks, Linux Systems, Kubernetes, Container technologies, REST API, UI skills, Strong programming skills like – C, C++, R, Python, Go Lang and well versed with Linux platform. Strong understanding of Data Science, modern tools and techniques to derive meaningful insights Understanding of Machine learning (ML) frameworks like scikit- learn, XGBoost etc. Understanding of Deep Learning (DL) Frameworks like Tensorflow, PyTorch Understanding of Deep Learning Compilers (DLC) Natural Language Processing (NLP) skills Understanding of different CPU architectures (little endian, big endian). Familiar with open source databases PostGreSQL, MongoDB, CouchDB, CockroachDB, Redis, data sources, connectors, data preparations, data flows, Integrate, cleanse and shape data. Preferred Technical And Professional Experience Preferred Technical Expertise: Practical working experience with Java, Python, GoLang, ReactJS, Knowledge of AI/ML/DL, Jupyter Notebooks, Storage Systems, Kubernetes, Container technologies, REST API, UI skills, Exposure to cloud computing technologies such as Red Hat OpenShift, Microservices Architecture, Kubernetes/Docker Deployment. Basic understanding of storage technologies: SAN, NAS, DAS Familiarity with RAID levels and disk configurations Knowledge of file systems (e.g., NTFS, ext4, ZFS) Experience with operating systems: Windows Server, Linux/Unix Basic networking concepts: TCP/IP, DNS, DHCP Scripting skills: Bash, PowerShell, or Python (for automation) Understanding of backup and recovery tools (e.g., Veeam, Commvault) Exposure to cloud storage: AWS S3, Azure Blob, or Google Cloud Storage

Introduction IBM Infrastructure division builds Servers, Storage, Systems and Cloud Software which are the building blocks for next-generation IT infrastructure of enterprise customers and data centers. IBM Servers provide best-in-class reliability, scalability, performance, and end-to-end security to handle mission-critical workloads and provide seamless extension to hybrid multicloud environments. India Systems Development Lab (ISDL) is part of word-wide IBM Infrastructure division. Established in 1996, the ISDL Lab is headquartered in Bengaluru, with presence in Pune and Hyderabad as well. ISDL teams work across the IBM Systems stack including Processor development (Power and IBM Z), ASCIs, Firmware, Operating Systems, Systems Software, Storage Software, Cloud Software, Performance & Security Engineering, System Test etc. The lab also focuses on innovations, thanks to the creative energies of the teams. The lab has contributed over 400+ patents in cutting edge technologies and inventions so far. ISDL teams also ushered in new development models such as Agile, Design Thinking and DevOps. Your Role And Responsibilities As a Software Engineer at IBM India Systems Development Lab (IBM ISDL), you will get an opportunity to work on all the phases of product development (Design/Development, Test and Support) across core Systems technologies including Operating Systems, Firmware, Systems Software, Storage Software & Cloud Software. As a Software Developer At ISDL: You will be focused on development of IBM Systems products interfacing with development & product management teams and end users, cutting across geos. You would analyze product requirements, determine the best course of design, implement/code the solution and test across the entire product development life cycle. One could also work on Validation and Support of IBM Systems products. You get to work with a vibrant, culture driven and technically accomplished teams working to create world-class products and deployment environments, delivering an industry leading user experience for our customers. You will be valued for your contributions in a growing organization with broader opportunities. At ISDL, work is more than a job - it's a calling: To build. To design. To code. To invent. To collaborate. To think along with clients. To make new products/markets. Not just to do something better, but to attempt things you've never thought was possible. Are you ready to lead in this new era of technology and solve some of the most challenging problems in Systems Software technologies? If so, let’s talk. Required Technical And Professional Expertise Systems and Cloud Software Engineer: As a Software Engineer with IBM Systems and Cloud Software teams, you will get the opportunity to get involved in all the phases of software development and work with technically accomplished teams. The responsibilities comprise of design new enhancements, coding (including test automation), problem determination and bug fixing, performance analysis, and solving client problems. You could also work on IBM Compute and Storage Systems including Virtualisation, I/O and Reliability Availability & Serviceability thereby, enabling the creation of a seamless software user experience across the stack delivering to IBM’s Hybrid Cloud and AI clients. As an engineer you will be responsible for enhancing and maintaining the key components of the Software stack, Platform enablement and an opportunity to work on closed and Open source development communities. Required Technical Expertise: Knowledge of Operating Systems, OpenStack, Kubernetes, Container technologies, Cloud concepts, Security, Virtualization Management, REST API, DevOps (Continuous Integration) and Microservice Architecture. Strong programming skills in C, C++, Go Lang, Python, Ansible, Shell Scripting. Comfortable in working with Github and leveraging Open source tools. AI Software Engineer: As a Software Engineer with IBM AI on Z Solutions teams, you will get the opportunity to get involved in delivering best-in class Enterprise AI Solutions on IBM Z and support IBM Customers while adopting AI technologies / Solutions into their businesses by building ethical, secure, trustworthy and sustainable AI solutions on IBM Z. You will be part of end to end solutions working along with technically accomplished teams. You will be working as a Full stack developer starting from understanding client challenges to providing solutions using AI. Required Technical Expertise: Knowledge of AI/ML/DL, Jupyter Notebooks, Linux Systems, Kubernetes, Container technologies, REST API, UI skills, Strong programming skills like – C, C++, R, Python, Go Lang and well versed with Linux platform. Strong understanding of Data Science, modern tools and techniques to derive meaningful insights Understanding of Machine learning (ML) frameworks like scikit- learn, XGBoost etc. Understanding of Deep Learning (DL) Frameworks like Tensorflow, PyTorch Understanding of Deep Learning Compilers (DLC) Natural Language Processing (NLP) skills Understanding of different CPU architectures (little endian, big endian). Familiar with open source databases PostGreSQL, MongoDB, CouchDB, CockroachDB, Redis, data sources, connectors, data preparations, data flows, Integrate, cleanse and shape data. Preferred Technical And Professional Experience Preferred Technical Expertise: Practical working experience with Java, Python, GoLang, ReactJS, Knowledge of AI/ML/DL, Jupyter Notebooks, Storage Systems, Kubernetes, Container technologies, REST API, UI skills, Exposure to cloud computing technologies such as Red Hat OpenShift, Microservices Architecture, Kubernetes/Docker Deployment. Basic understanding of storage technologies: SAN, NAS, DAS Familiarity with RAID levels and disk configurations Knowledge of file systems (e.g., NTFS, ext4, ZFS) Experience with operating systems: Windows Server, Linux/Unix Basic networking concepts: TCP/IP, DNS, DHCP Scripting skills: Bash, PowerShell, or Python (for automation) Understanding of backup and recovery tools (e.g., Veeam, Commvault) Exposure to cloud storage: AWS S3, Azure Blob, or Google Cloud Storage

Introduction IBM Infrastructure division builds Servers, Storage, Systems and Cloud Software which are the building blocks for next-generation IT infrastructure of enterprise customers and data centers. IBM Servers provide best-in-class reliability, scalability, performance, and end-to-end security to handle mission-critical workloads and provide seamless extension to hybrid multicloud environments. India Systems Development Lab (ISDL) is part of word-wide IBM Infrastructure division. Established in 1996, the ISDL Lab is headquartered in Bengaluru, with presence in Pune and Hyderabad as well. ISDL teams work across the IBM Systems stack including Processor development (Power and IBM Z), ASCIs, Firmware, Operating Systems, Systems Software, Storage Software, Cloud Software, Performance & Security Engineering, System Test etc. The lab also focuses on innovations, thanks to the creative energies of the teams. The lab has contributed over 400+ patents in cutting edge technologies and inventions so far. ISDL teams also ushered in new development models such as Agile, Design Thinking and DevOps. Your Role And Responsibilities As a Software Engineer at IBM India Systems Development Lab (IBM ISDL), you will get an opportunity to work on all the phases of product development (Design/Development, Test and Support) across core Systems technologies including Operating Systems, Firmware, Systems Software, Storage Software & Cloud Software. As a Software Developer At ISDL: You will be focused on development of IBM Systems products interfacing with development & product management teams and end users, cutting across geos. You would analyze product requirements, determine the best course of design, implement/code the solution and test across the entire product development life cycle. One could also work on Validation and Support of IBM Systems products. You get to work with a vibrant, culture driven and technically accomplished teams working to create world-class products and deployment environments, delivering an industry leading user experience for our customers. You will be valued for your contributions in a growing organization with broader opportunities. At ISDL, work is more than a job - it's a calling: To build. To design. To code. To invent. To collaborate. To think along with clients. To make new products/markets. Not just to do something better, but to attempt things you've never thought was possible. Are you ready to lead in this new era of technology and solve some of the most challenging problems in Systems Software technologies? If so, let’s talk. Required Technical And Professional Expertise Systems and Cloud Software Engineer: As a Software Engineer with IBM Systems and Cloud Software teams, you will get the opportunity to get involved in all the phases of software development and work with technically accomplished teams. The responsibilities comprise of design new enhancements, coding (including test automation), problem determination and bug fixing, performance analysis, and solving client problems. You could also work on IBM Compute and Storage Systems including Virtualisation, I/O and Reliability Availability & Serviceability thereby, enabling the creation of a seamless software user experience across the stack delivering to IBM’s Hybrid Cloud and AI clients. As an engineer you will be responsible for enhancing and maintaining the key components of the Software stack, Platform enablement and an opportunity to work on closed and Open source development communities. Required Technical Expertise: Knowledge of Operating Systems, OpenStack, Kubernetes, Container technologies, Cloud concepts, Security, Virtualization Management, REST API, DevOps (Continuous Integration) and Microservice Architecture. Strong programming skills in C, C++, Go Lang, Python, Ansible, Shell Scripting. Comfortable in working with Github and leveraging Open source tools. AI Software Engineer: As a Software Engineer with IBM AI on Z Solutions teams, you will get the opportunity to get involved in delivering best-in class Enterprise AI Solutions on IBM Z and support IBM Customers while adopting AI technologies / Solutions into their businesses by building ethical, secure, trustworthy and sustainable AI solutions on IBM Z. You will be part of end to end solutions working along with technically accomplished teams. You will be working as a Full stack developer starting from understanding client challenges to providing solutions using AI. Required Technical Expertise: Knowledge of AI/ML/DL, Jupyter Notebooks, Linux Systems, Kubernetes, Container technologies, REST API, UI skills, Strong programming skills like – C, C++, R, Python, Go Lang and well versed with Linux platform. Strong understanding of Data Science, modern tools and techniques to derive meaningful insights Understanding of Machine learning (ML) frameworks like scikit- learn, XGBoost etc. Understanding of Deep Learning (DL) Frameworks like Tensorflow, PyTorch Understanding of Deep Learning Compilers (DLC) Natural Language Processing (NLP) skills Understanding of different CPU architectures (little endian, big endian). Familiar with open source databases PostGreSQL, MongoDB, CouchDB, CockroachDB, Redis, data sources, connectors, data preparations, data flows, Integrate, cleanse and shape data. Preferred Technical And Professional Experience Preferred Technical Expertise: Practical working experience with Java, Python, GoLang, ReactJS, Knowledge of AI/ML/DL, Jupyter Notebooks, Storage Systems, Kubernetes, Container technologies, REST API, UI skills, Exposure to cloud computing technologies such as Red Hat OpenShift, Microservices Architecture, Kubernetes/Docker Deployment. Basic understanding of storage technologies: SAN, NAS, DAS Familiarity with RAID levels and disk configurations Knowledge of file systems (e.g., NTFS, ext4, ZFS) Experience with operating systems: Windows Server, Linux/Unix Basic networking concepts: TCP/IP, DNS, DHCP Scripting skills: Bash, PowerShell, or Python (for automation) Understanding of backup and recovery tools (e.g., Veeam, Commvault) Exposure to cloud storage: AWS S3, Azure Blob, or Google Cloud Storage

Location: Bengaluru (Hybrid) Role Summary We’re seeking a skilled Data Scientist with deep expertise in recommender systems to design and deploy scalable personalization solutions. This role blends research, experimentation, and production-level implementation, with a focus on content-based and multi-modal recommendations using deep learning and cloud-native tools. Responsibilities Research, prototype, and implement recommendation models: two-tower, multi-tower, cross-encoder architectures Utilize text/image embeddings (CLIP, ViT, BERT) for content-based retrieval and matching Conduct semantic similarity analysis and deploy vector-based retrieval systems (FAISS, Qdrant, ScaNN) Perform large-scale data prep and feature engineering with Spark/PySpark and Dataproc Build ML pipelines using Vertex AI, Kubeflow, and orchestration on GKE Evaluate models using recommender metrics (nDCG, Recall@K, HitRate, MAP) and offline frameworks Drive model performance through A/B testing and real-time serving via Cloud Run or Vertex AI Address cold-start challenges with metadata and multi-modal input Collaborate with engineering for CI/CD, monitoring, and embedding lifecycle management Stay current with trends in LLM-powered ranking, hybrid retrieval, and personalization Required Skills Python proficiency with pandas, polars, numpy, scikit-learn, TensorFlow, PyTorch, transformers Hands-on experience with deep learning frameworks for recommender systems Solid grounding in embedding retrieval strategies and approximate nearest neighbor search GCP-native workflows: Vertex AI, Dataproc, Dataflow, Pub/Sub, Cloud Functions, Cloud Run Strong foundation in semantic search, user modeling, and personalization techniques Familiarity with MLOps best practices—CI/CD, infrastructure automation, monitoring Experience deploying models in production using containerized environments and Kubernetes Nice to Have Ranking models knowledge: DLRM, XGBoost, LightGBM Multi-modal retrieval experience (text + image + tabular features) Exposure to LLM-powered personalization or hybrid recommendation systems Understanding of real-time model updates and streaming ingestion

Job Purpose Manage Electro-mechanical and Fire & Safety operations to ensure the quality and deliverables in a timely and cost effective manner at all office locations of Bangalore; Role would be responsible to build, deploy, and scale machine learning and AI solutions across GMR’s verticals. This role will build and manage advanced analytics initiatives, predictive engines, and GenAI applications — with a focus on business outcomes, model performance, and intelligent automation. Reporting to the Head of Automation & AI, you will operate in a high-velocity, product-oriented environment with direct visibility of impact across airports, energy, infrastructure and enterprise functions ORGANISATION CHART Key Accountabilities Accountabilities Key Performance Indicators AI & ML Development Build and deploy models using supervised, unsupervised, and reinforcement learning techniques for use cases such as forecasting, predictive scenarios, dynamic pricing & recommendation engines, and anomaly detection, with exposure to broad enterprise functions and business Lead development of models, NLP classifiers, and GenAI-enhanced prediction engines. Design and integrate LLM-based features such as prompt pipelines, fine-tuned models, and inference architecture using Gemini, Azure OpenAI, LLama etc. Program Plan Vs Actuals End-to-End Solutioning Translate business problems into robust data science pipelines with emphasis on accuracy, explainability, and scalability. Own the full ML lifecycle — from data ingestion and feature engineering to model training, evaluation, deployment, retraining, and drift management. Program Plan Vs Actuals Cloud , ML & data Engineering Deploy production-grade models using AWS, GCP, or Azure AI platforms and orchestrate workflows using tools like Step Functions, SageMaker, Lambda, and API Gateway. Build and optimise ETL/ELT pipelines, ensuring smooth integration with BI tools (Power BI, QlikSense or similar) and business systems. Data compression and familiarity with cloud finops will be an advantage, have used some tools like kafka, apache airflow or similar 100% compliance to processes KEY ACCOUNTABILITIES - Additional Details EXTERNAL INTERACTIONS Consulting and Management Services provider IT Service Providers / Analyst Firms Vendors INTERNAL INTERACTIONS GCFO and Finance Council, Procurement council, IT council, HR Council (GHROC) GCMO/ BCMO FINANCIAL DIMENSIONS Other Dimensions EDUCATION QUALIFICATIONS Engineering Relevant Experience 5 - 8years of hands-on experience in machine learning, AI engineering, or data science, including deploying models at scale. Strong programming and modelling skills in some like Python, SQL, and ML frameworks like scikit-learn, TensorFlow, XGBoost, PyTorch. Demonstrated ability to build models using supervised, unsupervised, and reinforcement learning techniques to solve complex business problems. Technical & Platform Skills Proven experience with cloud-native ML tools: AWS SageMaker, Azure ML Studio, Google AI Platform. Familiarity with DevOps and orchestration tools: Docker, Git, Step Functions, Lambda,Google AI or similar Comfort working with BI/reporting layers, testing, and model performance dashboards. Mathematics and Statistics Linear algebra, Bayesian method, information theory, statistical inference, clustering, regression etc Collaborate with Generative AI and RPA teams to develop intelligent workflows Participate in rapid prototyping, technical reviews, and internal capability building NLP and Computer Vision Knowledge of Hugging Face Transformers, Spacy or similar NLP tools YoLO, Open CV or similar for Computer vision. COMPETENCIES Personal Effectiveness Social Awareness Entrepreneurship Problem Solving & Analytical Thinking Planning & Decision Making Capability Building Strategic Orientation Stakeholder Focus Networking Execution & Results Teamwork & Interpersonal influence

Company Brief House of Shipping provides business consultancy and advisory services for Shipping & Logistics companies. House of Shipping's commitment to their customers begins with developing an understanding of their business fundamentals. We are hiring on behalf of one of our key US based client - a globally recognized service provider of flexible and scalable outsourced warehousing solutions, designed to adapt to the evolving demands of today’s supply chains. Currently House of Shipping is looking to identify a high caliber Data Science Lead . This position is an on-site position for Hyderabad . Background and experience: 15–18 years in data science, with 5+ years in leadership roles Proven track record in building and scaling data science teams in logistics, e-commerce, or manufacturing Strong understanding of statistical learning, ML architecture, productionizing models, and impact tracking Job purpose: To lead enterprise-scale data science initiatives in supply chain optimization, forecasting, network analytics, and predictive maintenance. This role blends technical leadership with strategic alignment across business units and manages advanced analytics teams to deliver measurable business impact. Main tasks and responsibilities: Define and drive the data science roadmap across forecasting (demand, returns), route optimization, warehouse simulation, inventory management, and fraud detection Architect end-to-end pipelines with engineering teams: from data ingestion, model development, to API deployment Lead the design and deployment of ML models using Python (Scikit-Learn, XGBoost, PyTorch, LightGBM), and MLOps tools like MLflow, Vertex AI, or AWS SageMaker Collaborate with operations, product, and technology to prioritize AI use cases and define business metrics Manage experimentation frameworks (A/B testing, simulation models) and statistical hypothesis testing Mentor team members in model explainability, interpretability, and ethical AI practices Ensure robust model validation, drift monitoring, retraining schedules, and version control Contribute to organizational data maturity: feature stores, reusable components, metadata tracking Own team hiring, capability development, project estimation, and stakeholder presentations Collaborate with external vendors, universities, and open-source projects where applicable Education requirements: Bachelor’s or Master’s or PhD in Computer Science, Mathematics, Statistics, Operations Research Preferred: Certifications in Cloud ML stacks (AWS/GCP/Azure), MLOps, or Applied AI Competencies and skills: Strategic vision in AI applications across supply chain Team mentorship and delivery ownership Expertise in statistical and ML frameworks MLOps pipeline management and deployment best practices Strong business alignment and executive communication

ML Solutions team within Markets OPS Technology is dedicated to developing solutions using Artificial Intelligence, Machine Learning and Generative AI. This team is a leader in creating new ideas, innovative technology solutions, and ground-breaking solutions for Markets Operations and Other Line of Businesses. We work closely with our clients and business partners to progress solutions from ideation to production by leveraging the entrepreneurial spirit and technological excellence. Job Description: The ML Solutions team is seeking a Data Scientist/Machine Learning Engineer to drive the design, development, and deployment of innovative AI/ML and GenAI-based solutions. In this hands-on role, you will leverage your expertise to create a variety of AI models, guiding a team from initial concept to successful production. A key aspect involves mentoring team members and fostering their growth. You will collaborate closely with business partners and stakeholders, championing the adoption of these advanced technologies to enhance client experiences, deliver tangible value to our customers, and ensure adherence to regulatory requirements through cutting-edge technical solutions. This position offers a unique opportunity to shape the future of our AI initiatives and make a significant impact on the organization. Key Responsibilities: Hands-On Execution and Delivery: Actively contribute to the development and delivery of AI solutions, driving innovation and excellence within the team. Take a hands-on approach to ensure AI models are successfully deployed into production environments, meeting high-quality standards and performance benchmarks. Mentoring Young Talents: Mentoring team, guiding data analysts/ML engineers from concept to production. This involves fostering technical growth, providing project oversight, and ensuring adherence to best practices, ultimately building a high-performing and innovative team. Quality Control: Ensure the quality and performance of generative AI models, conducting rigorous testing and evaluation. Research and Development: Participate in research activities to explore and advance state-of-the-art generative AI techniques. Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field. Cross-Functional Collaboration: Collaborate effectively with various teams, including product managers, engineers, and data scientists, to integrate AI technologies into products and services. Skills & Qualifications: 8 to 13 years of Strong hands-on experience in Machine Learning, delivering complex solutions to production. Experience with Generative AI technologies essential. Understanding of concepts like supervised, unsupervised, clustering, embedding. Knowledge of NLP, Name Entity Recognition, Computer Vision, Transformers, Large Language Models. In-depth knowledge of deep learning and Generative AI frameworks such as, Langchain, Lang Graph, Crew AI or similar. Experience with and other open-source frameworks/ libraries/ APIs like Hugging Face Transformers, Spacy, Pandas, scikit-learn, NumPy, OpenCV. Experience in using Machine Learning/Deep Learning: XGBoost, LightGBM, TensorFlow, PyTorch, Keras. Proficiency in Python Software Development, following Object-Oriented design patterns and best practices. Strong background in mathematics: linear algebra, probability, statistics, and optimization. Experience with evaluation, scoring with framework like ML Flow Experience of Docker container and edited a Docker file, experience with K8s is a plus. Experience with Postgres and Vector DBs a plus. Excellent problem-solving skills and the ability to think creatively. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams Publications and contributions to the AI research community are a plus. Master’s degree/Ph. D. or equivalent experience in Computer Science, Data Science, Statistics, or a related field. 8-12 years of experience This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills Data Science, Machine Learning. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi’s EEO Policy Statement and the Know Your Rights poster.