Data Scientist - Product, Play Monetization, Fraud and Abuse

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 years of work experience with a Master's degree).

Preferred qualifications:

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).

About the job

Google Play provides apps, games, and digital content services that bring Android devices to life. It is Google's approach to entertainment, syncing across your devices and the web.

In this role, you will be working on Google Play, doing everything from engineering our back-end systems, to shaping product strategy, and forming great content partnerships. You will make it possible for people to buy a game or eBook on their Android phone and have it instantly available on their laptop.

The Play Store serves over two billion users around the world and is a critical driver of Google’s overall business growth.

The US base salary range for this full-time position is $156,000-$229,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Partner with Program Managers, Engineering, and other Play teams to provide methodological excellence, data insights and tools that reduce risk and improve developer and user experience on Play.
• Support the product team to research and understand abusive behavior patterns, and be a thought partner to produce insights for technical and business stakeholders across Play.
• Ensure proper logging and metrics are available for performance measurement, and drive analysis focusing on product features and user experience across Play business generation.
• Work to develop frameworks to measure product success and provide insights at scale, and sharing recommendations to multiple levels of leadership, creating effective displays of quantitative information to aid decision making.
• Research and help to develop Machine Learning (ML) models, establishing evaluation criteria, and monitoring performance to combat fraudster adaptations.