Senior LIMS Business Analyst working on Starlims implementation for laboratory systems. Collaborating with analysts to enhance lab processes and engage stakeholders effectively.
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
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