Strava is the leading social platform for athletes and the largest sports community in the world, with US offices located in San Francisco and Denver and over 100 million athletes in 195 countries. If you sweat, you’re an athlete, and Strava’s mobile apps and website connect millions of active people every day. We are looking for an experienced analyst in a full-time role to be a key member of one of our cross-functional product teams. You will collaborate with product managers, engineers, designers, and researchers to accelerate learning, make data-informed decisions, and define data-inspired solutions to meet athlete needs. This role reports to an analytics manager and partners tightly with cross-functional collaborators throughout the company.
You’re excited about this opportunity because you will
- Analyze data to produce insights that shape our understanding of our athletes, their usage patterns, and opportunities to improve their experience.
- Collaborate closely with product managers and cross-functional partners to inform decisions and set strategy within a product team.
- Advise business partners on A/B test design and interpretation while upholding experimentation best practices within and across teams.
- Evaluate data tracking and quality on product surfaces, and collaborate with engineers to implement solutions where needed.
- Provide the “source of truth” for internal consumers by owning critical analytical reporting and building exploratory dashboards.
- Collaborate with the rest of the data organization at Strava (e.g. machine learning, data platform) to improve our technological craftsmanship.
We’re excited about you because
- You have 3+ years of experience in analytics, data science, or other quantitative domains. Experience in consumer-facing businesses is a plus.
- You are a strong communicator with an orientation towards impact, and you are comfortable working both cross-functionally and independently.
- You have a deep understanding of data pipeline concepts (e.g. ETL, scripting common analysis workflows).
- You are highly proficient with SQL and have experience with Business Intelligence tools (e.g. Tableau).
- You have hands-on experience with experimentation, including design, implementation, and methodologies (e.g. hypothesis testing and regression analysis) for analyzing and interpreting results to stakeholders.
- You have hands-on experience working with statistical programming languages (e.g. R, Python) for data wrangling and modeling.
- You are comfortable managing concurrent projects and meeting goals, even in the context of competing deadlines or priorities.