Product Data Science Manager

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree.
• 3 years of experience as a people manager within a technical leadership role.

Preferred qualifications:

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 4 years of experience as a people manager within a technical leadership role.
• Experience with developing machine learning models (supervised and unsupervised), launch experiments (A/B Testing), and end-to-end data infra and analytics pipelines.
• Experience in developing new models, methods, analysis and approaches, and with classification and regression, prediction and inferential tasks, training/validation criteria for ML algorithm performance.
• Prior business knowledge and understanding of monetization.

About the job

Google Play provides apps, games, and digital content services that bring Android devices to life. The Play Store serves over four billion users around the world, and is a critical driver of Google’s overall business growth.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

Responsibilities

• Synthesize complex insights across key domains (payments/FOP performance and retailing/ buyer activations) to shape product roadmaps, optimize purchase flows, and identify high-value opportunities.
• Define product success metrics, design advanced experimentation frameworks, and build scalable measurement views to ensure robust data integrity and proper logging.
• Direct and mentor a team of 5 Product Data Scientists, managing team roadmaps, resource allocation, and technical execution aligned with long-term goals.
• Partner with local Play BI, Play Apps and Games teams counterparts to foster a thriving local Data Science and Analytics community.
• Act as a critical thought partner to Product Management, Engineering, and Strategy teams, translating quantitative findings into actionable features and performance-measurement standards.