Senior Business Analyst

Strava

Senior Business Analyst driving user engagement and subscription growth at Strava. Collaborating across teams to leverage deep data analyses for retention and growth.

Posted 4/12/2026full-timeSan Francisco • California • 🇺🇸 United StatesSenior💰 $176,000 - $187,000 per yearWebsite

Tech Stack

Tools & technologies

ETLPythonSQLTableau

About the role

Key responsibilities & impact

Act as a go-to analytical expert for our User Lifecycle team, driving user engagement, retention and subscription growth.
Advise business partners on A/B test design and interpretation while upholding experimentation best practices.
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 (e.g. active users, retention rates).
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.
Analyze data to uncover insights that deepen understanding of the user journey.
Collaborate with the rest of the data organization at Strava (Machine Learning, Data Platform, etc.) to collectively improve our technological craftsmanship.

Requirements

What you’ll need

4+ years of full-time experience in analytics, data science, or other quantitative domains, preferably in consumer-facing tech.
Clear communicator with an orientation towards impact, comfortable working both multi-functionally and independently.
Deep understanding of data pipeline concepts (e.g. ETL, scripting common analysis workflows).
Highly proficient with SQL and experience with Business Intelligence tools (e.g. Tableau, Amplitude).
Experience defining and building key metrics and dimensions to monitor product and business performance.
Experience with experimentation and A/B testing, including design, implementation and methodologies (e.g. hypothesis testing and regression analysis).
Hands-on experience working with statistical programming languages (e.g. R, Python) for data wrangling and modeling.
Experience working on subscription or membership-based products, using data and insights to drive subscriber acquisition, engagement, and long-term retention.

Benefits

Comp & perks

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Hard Skills & Tools

data analysisA/B testingETLdata modelingSQLstatistical programmingdata wranglinghypothesis testingregression analysisbusiness performance metrics

Soft Skills

clear communicationimpact orientationcollaborationindependenceanalytical thinkingproblem-solvingstakeholder engagementtrend analysisinsight generationuser journey understanding