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Strava is a global community platform for active people with over 200 million athletes across 185+ countries. The Data Science team solves high-leverage business problems using machine learning, causal inference, and measurement systems to synthesize Strava's unique data assets into actionable models and metrics.
In this strategic individual contributor role, you will work across product and marketing teams to link their efforts to tangible outcomes for athletes and the business. You'll develop novel scientific approaches to measuring business performance, build causal frameworks and models, and help evolve metric strategy across the organization to ensure company-wide development points toward high-leverage outcomes.
Key responsibilities include:
- Design measurement strategies for Strava's most complex initiatives, applying experimental and quasi-experimental methods (geo testing, difference-in-differences, instrumental variables, synthetic control, etc.) to quantify business outcomes
- Expand understanding of relationships between user experiences and business performance; evolve organization-wide metric strategies connecting product development and marketing to high-quality results
- Lead deep root-cause investigations into business and product performance, developing novel approaches for problems without established playbooks
- Serve as domain expert in inference for the data team, reviewing measurement designs and raising the bar for causal evidence quality across data science, analytics, and cross-functional partners
Required qualifications:
- 5+ years in data science or related quantitative domain with experience owning measurement strategies and employing experimental and quasi-experimental methods
- Deep expertise in causal inference methods and their real-world failure modes, with judgment to assess credibility of each approach
- Strong SQL proficiency and comfort writing Python for statistical data processing
- Ability to write production-quality Python code for statistical analysis and experiment tooling
- Strong communication skills to present quantitative findings as clear narratives to technical and non-technical stakeholders in product, finance, and senior leadership
Strava operates a flexible hybrid model requiring more than half your time on-site in the San Francisco office—approximately three days per week. The company is backed by Sequoia Capital, TCV, Madrone Partners, and Jackson Square Ventures.
