Minimum qualifications:- Bachelor's degree in Statistics, Applied Mathematics, Data Science, Business Analytics, Economics or a related field and 5 years of progressive post-baccalaureate experience in the job offered or in a Data Scientist-related occupation.
- Alternatively, will accept a Master's degree in Statistics, Applied Mathematics, Data Science, Business Analytics, Economics or a related field, and 3 years of experience in the job offered or in a Data Scientist-related occupation.
- Position requires 3 years of experience in the following:
- Python or R for statistical analysis and data manipulation
- Product analysis, including root cause analysis and quantitative assessment of critical user journeys
- Translating open-ended business problems into structured analytical frameworks
- Defining and rationalizing metrics to measure product success and business outcomes
- Communicating quantitative insights to influence non-technical and senior leadership stakeholders
About the jobThe US base salary range for this full-time position is $194,850 - $237,000 15% bonus target equity benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Learn more about benefits at Google .
Position reports to the Google San Bruno, CA office & may allow for a hybrid schedule as per Google policy.
Responsibilities- Conduct end-to-end analysis using tools like SQL, R, and Python to solve ambiguous business problems and provide data-driven conclusions for projects and teams.
- Influence long-term product development strategies by providing analytical insights and actionable recommendations to cross-functional leadership and executive partners.
- Collaborate with stakeholders to translate and refine ambiguous business questions into tractable analyses, defining data requirements, methodologies, and evaluation metrics.
- Develop and prototype scalable analyses, business cases, and new processes, while advocating for necessary changes to data structures and metrics to support future needs.
- Define and report on Key Performance Indicators (KPIs) for business reviews, translating complex analysis results into clear business insights and product opportunities. Oversee data gathering and review analyses conducted by others, acting as a subject matter expert to anticipate challenges and ensure high-quality, validated data.
