Data Scientist, Discover
Summary
Builds and analyzes personalized recommendation feeds for 500M+ users, running A/B tests and growth accounting to improve engagement and retention.
US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
- Partner directly with Product Managers and Engineers to analyze user journeys, identify friction points across the funnel, and evaluate product interventions to improve activation, engagement, and retention.
- Build and maintain growth accounting frameworks to measure user dynamics (new, resurrected, retained, and churned users) across Discover's global user base.
- Lead the investigative cadence for weekly business reviews (WBR), identifying key drivers of week-over-week metric movements and presenting insights to cross-functional partners.
- Design, run, and evaluate A/B experiments on growth initiatives, ensuring excellence in measurement and decision-making.
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 work experience with a Master's degree.
- Experience with building and maintaining automated reporting pipelines and dashboards for recurring business reviews (such as WBRs).
- Experience in growth analytics, user lifecycle modeling, or growth accounting for consumer applications or feed-based recommendation systems.
- Experience partnering with product and engineering teams to translate investigative findings into product roadmaps and feature iterations.
Preferred qualifications:
- Master'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).