Hybrid Senior Business Analyst

at Strava

• Job title: Senior Business Analyst
• Job type: Full Time
• Experience level: Senior
• Salary: $176,000 - $187,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: ETL, Python, SQL, Tableau
• Location requirements: Hybrid, San Francisco, United States

About the role

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

Responsibilities

• 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

• 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

• Offers Equity