SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Strava is a global fitness platform with over 200 million active users across 185+ countries. The Sport Science team sits at the executive level, reporting directly to the CEO, and is responsible for scientific validation, safety review, and applied research for Strava's and Runna's (Strava's coaching platform) fitness products.
As Head of Sport Science, you will own two core responsibilities: (1) ongoing scientific validation and safety review of Runna's and Strava's fitness products, including active academic audits; and (2) the applied research agenda that advances the science of sport and fitness.
Key responsibilities include:
- Lead scientific validation and safety review processes for fitness products, managing active academic audits
- Manage and grow academic partnerships with Stanford University and Loughborough University; scope and establish new partnerships as needed
- Define data and labeling strategies (perceived exertion, injury history, sleep, etc.) that make AI/ML model insights scientifically defensible
- Partner with Runna's coaching team on recurring scientific review cadences, serving as the authority on science application in coaching
- Build out the Sport Science team and establish an external academic advisory council
- Represent Strava's scientific credibility externally through published research, conference talks, and media appearances
- Work cross-functionally with coaching, AI/ML, Data Science, Product, Public Policy, and Legal teams
The role operates on a flexible hybrid model requiring more than half your time on-site in San Francisco (three days per week minimum).
REQUIREMENTS:
- MD, PhD, or equivalent applied track record in exercise physiology, sports science, biomechanics, sports medicine, or closely related field
- Substantial experience combining peer-reviewed research with applied work in industry, elite sport, or research-focused sports medicine setting, with demonstrated ability to translate science into product decisions
- Track record managing external academic or clinical partnerships, including agreements, multi-institution collaborations, and ethics-related governance
- Plus factors: comfort partnering with data science and ML teams to translate research questions into model and data requirements (coding not required); experience building a team or function from first hire; track record representing scientific work externally (publications, conference talks, podcasts); endurance or running-specific research experience
