33 Pymc3 Jobs - Page 2

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!

Freelance Opportunity: Statistician – Predictive Modeling & Advanced Analytics (Remote | ₹70,000/month) 📅 Duration: 3-Month Contract (Renewable) 💰 Compensation: ₹70,000/month (net, based on deliverables) We’re hiring a freelance statistician who loves building powerful predictive models using advanced statistical and machine learning techniques. If you’re skilled in Bayesian modeling , clustering algorithms , and discrete choice models , and enjoy solving complex real-world problems, we’d love to work with you! 🔍 What You'll Work On: Bayesian probabilistic models (PyMC3, Stan, etc.) Advanced regression (GLM, regularized, hierarchical) Clustering algorithms: AHC, KNN, LCA, SVM, SOM Discrete Choice Modeling: MNL, Nested Logit, Mixed Logit ML techniques for prediction, segmentation, classification Clear documentation and delivery of code + insights ✅ What We’re Looking For: Postgrad in Statistics, or Mathematics field - This is a must have, preferably from ISI or such Institutes. Strong in Python and/or R (esp. NumPy, pandas, scikit-learn) Practical experience with Bayesian tools, ML libraries Bonus if you’ve worked in consumer research or behavior modeling Self-driven, reliable, and outcome-focused 📌 How It Works: Remote, freelance contract Work independently with regular check-ins Monthly payment based on pre-agreed deliverables Show more Show less

Data Engineer – GCP & PySpark (Iceberg/BigQuery) || 4-7 years Location: Noida (In-office/Hybrid; client site if required) Experience: 4–7 years Type: Full-Time | Immediate Joiners Preferred Client: Leading Canadian-based Tech Company Must-Have Skills: GCP (BigQuery, Dataflow, Dataproc, Cloud Storage) PySpark / Spark – Distributed computing expertise Apache Iceberg (preferred), Hudi, or Delta Lake Role Overview: Be part of a high-impact Data Engineering team focused on building scalable, cloud-native data pipelines. You'll support and enhance EMR platforms using DevOps principles , helping deliver real-time health alerts and diagnostics for platform performance. Key Responsibilities: Provide data engineering support to EMR platforms Design and implement cloud-native, automated data solutions Collaborate with internal teams to deliver scalable systems Continuously improve infrastructure reliability and observability Technical Environment: Databases: Oracle, MySQL, MSSQL, MongoDB Distributed Engines: Spark/PySpark, Presto, Flink/Beam Cloud & Infra: GCP (preferred), AWS (nice-to-have), Terraform Big Data Formats: Iceberg, Hudi, Delta Tools: SQL, Data Modeling, Palantir Foundry, Jenkins, Confluence Bonus: Stats/math tools (NumPy, PyMC3), Linux scripting Ideal for engineers with cloud-native, real-time data platform experience — especially those who have worked with EMR and modern lakehouse stacks. Job Type: Full-time Pay: Up to ₹1,000,000.00 per year Application Question(s): What is your notice period (in Days)? What is your current annual compensation (in INR)? What is your expected annual salary (in INR)? Experience: GCP services like BigQuery, Dataflow, or Dataproc: 7 years (Required) developing or maintaining Spark or PySpark jobs: 7 years (Required) Apache Iceberg : 7 years (Required) EMR or similar big data platforms: 7 years (Required) Terraform projects: 7 years (Required) SQL development and data modeling: 7 years (Required) Location: Noida, Uttar Pradesh (Required) Work Location: In person