Job Description

Strava is the app for active people. With over 150 million athletes in more than 185 countries, its more than tracking workoutsits where connection, motivation, and personal bests thrive. No matter your activity, gear, or goals, Stravas got you covered. Find your crew, crush your milestones, and keep moving forward. Start your journey with Strava today.

As a Lead Data Scientist , you will play a key role in shaping the future of data-driven decision-making at Strava. You will develop and deploy cutting-edge machine learning models, design rigorous experimentation frameworks, and uncover insights that drive impactful business and product decisions. Working alongside cross-functional teams, you will help harness Stravas vast dataset to enhance athlete experiences and drive engagement.

We follow a flexible hybrid model that generally translates to around half your time on-site in our San Francisco officeroughly three days per week.

Youre excited about this opportunity because you will:

• Develop and enhance machine learning models, leveraging supervised, unsupervised, and reinforcement learning techniques to enhance the athlete experience on Strava continuously.
• Design and implement experimentation strategies, such as A/B testing and causal inference, to drive data-informed product and business decisions.
• Work closely with product managers, engineers, marketing teams, and other partners to develop data-driven solutions that improve athlete engagement and business outcomes.
• Apply expertise in large-scale data analysis to identify trends, uncover opportunities, and inform strategic decision-making.
• Stay ahead of the latest industry trends in machine learning, LLMs, transformers, and deep learning, evaluating their potential impact on Stravas data capabilities.
• Mentor other data scientists, contribute to knowledge sharing through blog posts or tech talks, and help uplevel the data science capabilities.

You will be successful here by:

• Demonstrating technical excellence in machine learning, data analysis, and experimentation methodologies.
• Driving collaboration across teams to ensure data science solutions align with business goals.
• Communicating complex data concepts effectively to both technical and non-technical stakeholders.
• Continuously seeking opportunities to optimize and innovate Stravas data science practices.
• Championing a culture of learning, mentorship, and knowledge sharing within the data science team.

Were excited about you because:

• Educational Background : You have an MS degree or equivalent experience in Computer Science, Mathematics, Statistics, or a related quantitative field.
• Experience : You bring 5+ years of experience in data science roles, with a consistent track record of driving impactful solutions.
• Machine Learning Expertise : You have hands-on experience with various ML techniques, including supervised and unsupervised learning, and are comfortable working with deep learning models such as transformers or LLMs.
• Experimentation & Statistical Analysis : You have a solid grasp of A/B testing, causal inference, and statistical methodologies to support meticulous data-driven decision-making.
• Cloud & Deployment : You have experience deploying ML models in production using cloud platforms like AWS (or equivalent).
• Analytical & Problem-Solving Skills : You excel at taking on complex problems, uncovering insights, and driving data-driven strategies.
• Communication & Collaboration : You are skilled at explaining complex data concepts to diverse audiences and thrive in a cross-functional environment.

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