Lead Data Scientist, Experimentation Platform

About the role

You architect and own the end to end roadmap for the experimentation platform, defining how measurement, analysis, and insights scale across product and marketing. You translate ambiguous business questions into rigorous experimental designs that withstand real world complexity and stakeholder scrutiny. You partner deeply with engineers and product leaders to turn strategic intent into executable test strategies that generate trustworthy evidence. You evangelize best practices in causal inference so that the organization learns faster and with greater confidence. You balance methodological rigor with shipping velocity, ensuring that experiments deliver actionable insights without blocking innovation. You mentor analysts and data scientists on robust evaluation techniques and help elevate the standard of evidence across the company. You steward the data infrastructure that powers experimentation, ensuring reliability, transparency, and scalability for a global audience.

Key facts

What you'll do

Design and own the end to end experimentation roadmap for a consumer product serving tens of millions of athletes worldwide.

Partner with engineers, product managers, and marketers to translate business objectives into rigorous experimental strategies and execution plans.

Collaborate closely with Comms and platform engineers to expand technical capabilities for serving and measuring experiences across athlete touchpoints.

Define and standardize methods for hypothesis testing, noninferiority testing, incremental lift estimation, power analysis, and program level holdouts.

Lead the evaluation of program level experiments while diagnosing interaction effects, winner's curse, and other threats to valid learning.

Serve as a domain expert to horizontally support data initiatives related to experimentation, measurement, and causal inference.

Establish processes and documentation that enable cross functional teams to design, execute, and interpret high quality experiments.

Champion measurement frameworks and metrics that reflect real world impact on athlete behavior and business outcomes.

Work with stakeholders to prioritize experiments, manage tradeoffs, and maintain a roadmap that balances learning with user experience.

Build tools and dashboards that improve visibility into experiment performance, health metrics, and long term outcomes.

Champion a culture of evidence based decision making by training and advising teams on robust evaluation practices.

Partner with data infrastructure teams to ensure experimentation data is reliable, well documented, and scalable.

Define guardrails and best practices for sample size, timing, and targeting to maximize insight while protecting user experience.

Lead postmortems and learning loops that turn experiment results into concrete process improvements.

Requirements

5+ years of experience in data science or a related quantitative domain with hands on experience working on experiments, preferably with back end knowledge of experimentation systems.

Deep familiarity with methodology and common issues in scaling experimentation, including hypothesis and noninferiority testing, incremental lift estimation, power estimation, program level holdout experiments, winner's curse, and interaction effects.

Strong SQL proficiency and comfort writing software for statistical data processing.

Fluency in metrics and measurement for consumer software products, and comfort working with cross functional partners to translate business needs into technical plans and vice versa.

Experience building and maintaining experimentation platforms or core measurement infrastructure in a high traffic consumer environment.

Strong communication skills and the ability to influence without authority through clear narratives and data driven recommendations.

Ability to thrive in a fast paced, ambiguous environment while maintaining rigorous analytical standards.

Nice to have

Experience with back end systems and data pipelines that support large scale experimentation.

Deep knowledge of causal inference methods beyond basic A B testing, such as difference in differences, regression discontinuity, or instrumental variables where appropriate.

Experience with experimentation tools and feature flag systems commonly used in consumer products.

Background in consumer product analytics, especially in fitness, health, or social platforms.

Experience contributing to open source or internal tooling for experimentation and measurement.

Practical notes

This role follows a flexible hybrid model requiring three days per week in the Strava San Francisco office.

About Strava

Movement brings us together. At Strava, we're building the world's largest community of active people, helping them stay motivated and achieve their goals.

Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you're shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact.

When you join Strava, you're not just joining a company you're joining a movement. If you're ready to bring your energy, ideas, and drive, let's build something incredible together.

Strava builds software that makes the best part of our athletes' days even better. Just as we're deeply committed to unlocking their potential, we're dedicated to providing a world class, inclusive workplace where our employees can grow and thrive, too. We're backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we're expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together.

Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy related condition, marital status, height and or weight.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform