Senior Data Scientist, Product, Android App Safety

Key Skills

Data science techniques, KPI, Product Management, Python Programming, R Programming, SQL

Job Description

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 work experience plus 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 experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
• Experience translating product and business questions into clearly framed investigative projects, extracting and manipulating large datasets, and applying statistical methods.
• Knowledge of data, metrics, analysis, trends, measurement, statistics and program evaluation, with the ability to solve large, complex problems.
• Ability to present to executives and communicate effectively with highly technical leadership teams.
• Ability to manage multiple assignments simultaneously in a fluid environment.

About the job

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.

Responsibilities

• Work with large, complex internal data sets, solve difficult, non-routine analysis problems, applying advanced investigative methods as needed.
• Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables and presentations.
• Work with stakeholders in Product Management, Engineering and Operation teams to define performance goals, Key Performance Indicators (KPI) and other success measurements.
• Develop, own and evolve investigative frameworks providing source of truth measures for the organization.
• Conduct deep dives revealing opportunities and risks, enabling the team to understand trends and prioritize resources.