Senior Data Scientist, Experimentation - job 1 of 2
Skills
- Strong statistical analysis and causal inference expertise
- Proficient programming in Python and SQL
- Experience designing and analyzing A/B tests at scale
- Machine learning model development and deployment experience
- Data visualization and dashboarding skills
- Ability to translate analytics into clear business recommendations
- Experience collaborating with cross-functional engineering and product teams
Responsibilities
- Design, plan, implement, and analyze A/B experiments and causal inference studies to evaluate product changes
- Perform deep-dive analyses to identify product growth opportunities and recommend metric-driven improvements
- Define and maintain key product performance metrics and build scalable dashboards to monitor them
- Build clear data visualizations and narratives to communicate insights to product, engineering, and senior leadership
- Lead large-scale analytics projects to uncover user insights and inform product strategy
- Partner with Product, Engineering, Operations, and cross-functional teams to embed data-driven decision-making
- Contribute to, document, and promote experimentation best practices and standardized methods
Education
- Master’s or PhD in a quantitative field (mathematics, statistics, engineering, computer science, or natural sciences)
- Extensive practical experience (see years of experience requirements below) developing and deploying predictive models and experiments
Benefits
- Performance-driven compensation with bonus opportunities and equity
- 401(k) matching
- 100% paid employee health insurance and ~90% dependent coverage
- Lifestyle wallet for wellness, learning, and more
- Employer-paid life & disability insurance, fertility and mental health benefits
- Generous paid time off, parental leave, and company holidays
- Catered office experience, events, and comfortable workspaces
Average salary estimate
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