About the company
Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count.
Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward.
Responsibilities
- Define and own the domain strategy and roadmap for ranking, recommendations, and personalization across Strava's core athlete experiences.
- Identify and prioritize high-value GenAI and ML product opportunities across the app, and build a pipeline of bets that connect to company-level priorities.
- Partner closely with ML engineering and data science to translate model capabilities, evaluation criteria, and technical trade-offs into clear, shippable product decisions.
- Build and drive experimentation and measurement frameworks that demonstrably improve relevance, engagement, and athlete outcomes.
- Align stakeholders across Product, Engineering, and Design on strategy and priorities, resolving ambiguity and keeping complex initiatives moving.
- Contribute to the broader AI/ML product strategy, including identifying where generative AI can meaningfully improve the athlete experience across Strava's surfaces.
Requirements
- Substantial product management experience, including meaningful time shipping ML-powered products such as ranking, recommendations, personalization, search, or feeds at scale.
- Deep fluency in modern ML and generative AI — enough to engage substantively with engineers and data scientists on models, evaluation, and data pipelines, and to make sound product trade-offs.
- A track record of owning domain-level strategy end-to-end, not just executing within a defined roadmap.
- Strong experimentation and measurement instincts, with demonstrated ability to use data to drive measurable improvements in relevance and engagement.
- The ability to align and influence senior stakeholders across functions without authority, and to bring clarity to complex, ambiguous problem spaces.
- A low-ego, partnership-oriented approach to working with technical and design partners.
- Experience productizing emerging or research-stage capabilities into reliable, user-facing features is a plus.
Conditions
- We follow a flexible hybrid model that translates to more than half of your time on-site in our San Francisco office, three days per week.
- For more information on benefits please click here.