Sr. Analyst, Product Analytics

PlayStation Global•San Mateo, CA

20h•$175,013 - $248,900•Onsite

About The Position

Sony Interactive Entertainment LLC seeks a Sr. Analyst, Product Analytics in San Mateo, CA to support the planning and rollout of large-scale testing strategies, including segmentation, global holdouts, and longitudinal studies. This role involves developing and deploying machine learning models for user segmentation, behavior prediction, and fraud detection. The analyst will design and analyze experiments using various frameworks, interpret results across user segments, and mitigate validity threats. They will also perform causal impact measurement and competitor analysis using quasi-experimental and time-series techniques. Building and maintaining dashboards, managing data pipelines, validating metrics, and supporting experimentation scalability are key responsibilities. The role requires expertise in digital user behavior and monetization analytics, applying data mining and behavioral segmentation for optimization decisions, and utilizing a range of programming languages and data platforms.

Requirements

Master’s degree in Business Analytics, or related field or equivalent.
Three (3) years of experience developing and deploying machine learning modeling for user segmentation, behavior prediction, and fraud detection using Random Forest, Gradient Boosted Trees (XGBoost), Logistic Regression, K-Means, DBSCAN, Latent Class Analysis, and association rule mining.
Experience designing and analyzing experiments across A/B testing, multivariate testing, frequentist frameworks, and Bayesian experimentation.
Experience designing multi-dimensional test structures and interpreting results across user segments.
Experience mitigating validity threats including SRM, contamination, and multi-exposure through stratified sampling and CUPED adjustment.
Experience performing causal impact measurement and competitor analysis using quasi-experimental methods including Synthetic Control Models, and time-series techniques including Difference-in-Differences, Interrupted Time Series, Bayesian Structural Time Series models, Seasonal-Trend Decomposition, and Rolling Regression.
Experience building and maintaining dashboards using Tableau/DOMO to integrate ETL processes.
Experience troubleshooting technical configurations, managing data pipelines, validating metrics, and supporting experimentation scalability.
Experience utilizing digital user behavior and monetization analytics, including online customer journeys, website conversions, payment-related user interactions, retention analysis, churn modeling, and marketing return on investment (ROI).
Experience applying data mining and behavioral segmentation techniques to uncover patterns that drive product, marketing, and revenue optimization decisions.
Proficiency in Python, R, SQL, Adobe Analytics, Customer Journey Analytics, and cloud-based data platforms including Databricks, Data Ocean, Redshift, AWS S3, MongoDB, data catalog and Postgres to manage and analyze large-scale datasets.

Responsibilities

Support the planning and rollout of large-scale testing strategies, including segmentation, global holdouts, and longitudinal studies.
Develop and deploy machine learning modeling for user segmentation, behavior prediction, and fraud detection using Random Forest, Gradient Boosted Trees (XGBoost), Logistic Regression, K-Means, DBSCAN, Latent Class Analysis, and association rule mining.
Design and analyze experiments across A/B testing, multivariate testing, frequentist frameworks, and Bayesian experimentation.
Design multi-dimensional test structures and interpret results across user segments.
Mitigate validity threats including SRM, contamination, and multi-exposure through stratified sampling and CUPED adjustment.
Perform causal impact measurement and competitor analysis using quasi-experimental methods including Synthetic Control Models, and time-series techniques including Difference-in-Differences, Interrupted Time Series, Bayesian Structural Time Series models, Seasonal-Trend Decomposition, and Rolling Regression.
Build and maintain dashboards using Tableau/DOMO to integrate ETL processes.
Troubleshoot technical configurations, manage data pipelines, validate metrics, and support experimentation scalability.
Utilize digital user behavior and monetization analytics, including online customer journeys, website conversions, payment-related user interactions, retention analysis, churn modeling, and marketing return on investment (ROI).
Apply data mining and behavioral segmentation techniques to uncover patterns that drive product, marketing, and revenue optimization decisions.
Manage and analyze large-scale datasets using Python, R, SQL, Adobe Analytics, Customer Journey Analytics, and cloud-based data platforms including Databricks, Data Ocean, Redshift, AWS S3, MongoDB, data catalog and Postgres.