Google

Minimum qualifications:

• Bachelor's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
• 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience with a Master's degree).
• 7 years of experience with statistical data analysis.
• 5 years of experience with data mining, querying, and managing investigative projects.
• 3 years of experience developing and managing metrics or evaluating programs/products.

Preferred qualifications:

• Master's degree in a quantitative field such as; Statistics, Computer Science, Engineering, Mathematics, Economics, or Physics.
• 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
• 7 years of experience with statistical data analysis, modeling, experimentation, and causal inference.
• 5 years of experience with data mining, querying, and managing analytical projects.
• 3 years of experience developing and managing metrics or evaluating programs/products.
• Experience working on unstructured business problems with data science, translating into impactful business recommendations, and measuring the success of those initiatives.

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.

With a combination of sharp investigative skills and keen commercial acumen, the Play Games Data Science and Analytics (DSA) team provides the insights and operational that enable Play to delight users, empower developers and create value for Google. As strategic advisors, we collaborate with Product, Engineering, Marketing and other teams in support of Play's loyalty-focused products, including Play Points and Play Pass.

We are seeking a highly motivated Data Scientist to join our expanding team. In this role, you will gather context into various aspects of Play by collaborating with other DSA/PM/Engineering teams, exercise deep curiosity, employ investigative and data science skills and business acumen to identify growth opportunities for Play. You will contribute to creating and executing on a X-Play data science roadmap and be seen as a go-to leader that can be called on to solve some of the most complex and high value data science problems in Play. You will also serve as an expert data scientist and contribute to creating the requirements for the Data Engineering team in establishing analytical data marts, pipelines and data governance best practices to serve the Play DSA team.

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.

The US base salary range for this full-time position is $183,000-$271,000 + 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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide investigative thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).
• Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of analytical/statistical models, and presentation to stakeholders.
• Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generate hypotheses, and make recommendations from a perspective that combines both, investigative and product-specific expertise.
• Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.
• Directly or indirectly oversee the contributions of others and develop colleagues’ capabilities in the area of specialization.