The Health Data Science Team (Insights and Analytics) drives transformative growth by providing an engaged edge, inspiring action, and shaping the future of our business. Our mission is to inspire and deliver transformational action for our products and business with the customer at the center. We illuminate consumer, market, and product understanding to accelerate Google Health and Fitbit’s goal of making everyone in the world healthier. We do this by providing deep expertise and objectivity in product Data Science. A unified view of consumer and market opportunity across the Google and Fitbit portfolio, including devices, mobile app, and Google Health subscription.
As a Data Scientist (Product), you will see different angles of a product or business opportunity, and you will know how to connect the dots and interact with people in various roles and functions. You will work to effectively turn business questions into data analysis, and provide meaningful recommendations on product and strategy. You will provide quantitative analysis, product expertise and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you will serve as an analytics expert for your partners, using quantitative insights to help them make better decisions. You will create stories with meaningful insight from data. You will make key recommendations for our partners in Product Management, Engineering, and Business Development and Strategy.
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 $138,000-$198,000 + 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
- Drive analysis to contribute to shaping the future of the new AI-powered personal health coach, built with Gemini and possessing expertise that adapts based on users’ personal health and wellness data.
- Inform key product decisions, focused on improving product usability, and users’ adoption, engagement, and satisfaction. Focus on core product and intelligence features, user segmentation, and relation to user satisfaction.
- Drive analysis and experimentation for full funnel optimization, including attach rate, conversion rate and lifetime value, with a particular focus on growing the Fitbit subscription business. Help drive key decisions to improve Google Health products and services.
- Deliver effective presentations of recommendations to stakeholders. Conduct data analysis to make business recommendations.
- Develop and automate reports and dashboards to provide insights at scale. Use causal inference to quantify impact on product improvements.
Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) or 2 years of experience with a Master's degree.
Preferred qualifications:
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 5 years of experience with statistical data analysis, modeling, experimentation, and causal inference to solve product and business problems.
- Experience in extracting and analyzing large sets of data with SQL and in designing Extract, Transform, and Load (ETL) flows.
- Experience in applying AI/ML to Data Science questions, from inception to completion.
- Excellent programming skills in SQL and Python.
- Proven track record of solving unstructured business problems with data science, translating results into impactful business recommendations, and measuring the success of those initiatives.