Product Analyst

Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count.

Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward.

• 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 product 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.
• Own end-to-end data solutions including: data instrumentation, ETL and modeling and developing dashboards.
• Proactively surface trends and insights, quantify the impact, and translate them into clear actions for stakeholders.
• Collaborate with the rest of the data organization at Strava (e.g. data science, data engineering) to improve our technological craftsmanship.

• You have 4+ years of full-time experience in analytics, data science, or other quantitative domains, preferably in consumer-facing tech.
• You are a clear communicator with an orientation towards impact, and you are comfortable working both multi-functionally and independently.
• You have a deep understanding of data pipeline concepts (e.g. ETL, scripting common analysis workflows, DBT).
• You are highly proficient with SQL and have experience with Business Intelligence tools (e.g. Omni).
• You have experience defining and building key metrics and dimensions to monitor product and business performance, ensuring they accurately reflect user behavior and drive decisions.
• You have experience with experimentation and A/B testing, including design, implementation and methodologies (e.g. hypothesis testing and regression analysis) for analyzing and interpreting results.
• 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.

• We follow a flexible hybrid model that translates to more than half of your time on-site in our San Francisco office — three days per week.