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Senior Product Analyst – User Lifecycle
| Company | Strava |
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| Location | San Francisco, CA, USA |
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| Salary | $155000 – $182000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s |
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| Experience Level | Senior |
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Requirements
- 4+ years of full-time experience in analytics, data science, or other quantitative domains, preferably in consumer-facing tech.
- Graduated with a Bachelor’s degree in a quantitative field such as math, statistics, physics, economics or data science.
- Deep understanding of data pipeline concepts (e.g. ETL, scripting common analysis workflows).
- Highly proficient with SQL and have experience with Business Intelligence tools (e.g. Tableau, Amplitude).
- Experience defining and building key metrics and dimensions to monitor product and business performance, ensuring they accurately reflect user behavior and drive decisions.
- Experience with experimentation and A/B testing, including design, implementation and methodologies (e.g. hypothesis testing and regression analysis) for analyzing and interpreting results.
- Hands-on experience working with statistical programming languages (e.g. R, Python) for data wrangling and modeling.
- Comfortable managing concurrent projects and meeting goals, even in the context of competing deadlines and priorities.
Responsibilities
- Analyze data to produce insights that shape our understanding of the user journey, from onboarding to becoming an engaged, long-term user, identifying opportunities to improve conversion, strengthen habits, and drive retention.
- 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 (Machine Learning, Data Platform, etc.) to collectively improve our technological craftsmanship.
Preferred Qualifications
No preferred qualifications provided.
