Senior Data Scientist

About the Role

Key Responsibilities

• Develop and enhance machine learning models using supervised, unsupervised, and reinforcement learning techniques to continuously elevate the athlete experience on Strava.
• Design and implement robust experimentation strategies—including A/B testing, causal inference, and advanced techniques such as quasi-experimental designs—to drive data-informed product and business decisions.
• Build and operationalize models for key business and product challenges, including propensity modeling, lifetime value (LTV) prediction, forecasting, and user segmentation.
• Collaborate cross-functionally with product managers, engineers, marketers, and other stakeholders to develop and scale data-driven solutions that improve athlete engagement and business outcomes.
• Apply expertise in large-scale data analysis to identify behavioral trends, surface growth opportunities, and inform strategic direction.
• Stay current with advances in machine learning and AI—including transformers, LLMs, and deep learning—to explore their application in improving Strava's data and product capabilities.

Requirements

• Educational background with an MS degree or equivalent experience in Computer Science, Mathematics, Statistics, or a related quantitative field.
• 3+ years of experience in data science roles, with a track record of driving impactful solutions.
• Hands-on experience with various ML techniques, including supervised, unsupervised learning, reinforcement learning, and deep learning models such as transformers or LLMs.
• Solid grasp of A/B testing, causal inference, and statistical methodologies to support data-driven decision-making.
• Experience deploying ML models in production using cloud platforms like AWS (or equivalent).
• Strong analytical and problem-solving skills to uncover insights and drive strategies.
• Excellent communication and collaboration skills, with the ability to explain complex data concepts to diverse audiences.

Nice to Have

• Experience with large-scale data analysis and data engineering.
• Familiarity with additional cloud platforms or deployment tools.
• Knowledge of advanced AI techniques and emerging technologies in machine learning.

Qualifications

• MS degree or equivalent experience in a relevant quantitative field.
• 3+ years of professional experience in data science roles.

Benefits & Perks

• Competitive salary range of $209,000 - $222,000 (base only, excluding benefits and equity).
• Flexible hybrid work model with approximately three days per week on-site in San Francisco.
• Participation in total rewards programs reflecting market-based pay.
• Opportunity to work in a passionate, innovative, and inclusive environment.
• Being part of a global community dedicated to movement and active lifestyles.