Senior Product Analyst

We are looking for an experienced analyst in a full-time role to be a key member of one of our cross-functional product teams. You will collaborate with product managers, engineers, designers and researchers to accelerate learning, make data-informed decisions and define data-inspired solutions to meet athlete needs. This role reports to an analytics manager and partners tightly with cross-functional stakeholders throughout the company.

Responsibilities

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.

Requirements

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.