Data Scientist, Product Analytics

Peloton
New York, New YorkPosted 11 April 2026

Job Description

About the Role Peloton is entering a transformative new chapter. We are evolving from a pioneer in connected fitness into a comprehensive wellness ecosystem, powered by innovation and data. Our mission remains steadfast: to empower our global community to lead healthier, happier, and fitter lives. As we redefine the future of health, we are looking for leaders who are eager to build the frameworks that will support this next generation of world-class member experiences. As a user- centered, outcomes-driven Product organization, Peloton relies on the Product Analytics team to deliver strategic insights, reporting capabilities and A/B testing to inform our direction product roadmap. The analyst will champion the wide range of monetization product analytics designed to profitably grow Peloton’s member engagement and spearhead the analytical initiatives designed to optimize the product strategy. Peloton is seeking a Product Analyst to join the Product Analytics team, focused on driving member engagement through habit formation. At Peloton, our goal is to create Members for Life —building lasting fitness routines that become an integral part of our members’ daily lives. To support this, we are investing in product experiences designed to help members build and sustain consistent fitness habits. This role will play a critical part in evaluating whether these experiences are meaningfully improving member behavior and long-term engagement. The Product Analyst will partner closely with cross-functional product teams to measure impact, uncover insights, and shape product strategy—ensuring our work translates into durable habit formation and stronger member retention. You Will: Own analytics for habit formation engagement features—from defining success metrics to surfacing insights that drive product decisions Partner with PMs and Designers to build, launch, and measure A/B tests that influence the roadmap Tell compelling stories with data: create clear narratives that influence senior stakeholders and help guide strategic direction Translate member behavior into actionable insights that improve retention and long-term engagement Advocate for clean, consistent data instrumentation and support experimentation best practices You Bring: 3–5 years of analytics experience, with a focus on product or UX analytics (experience in fitness or consumer tech is a plus) Fluency in SQL and comfort with Python (e.g. pandas, numpy) for data exploration Experience designing and analyzing A/B tests and interpreting results with statistical rigor Proven ability to influence product strategy through compelling data storytelling Comfort working autonomously and collaboratively in a fast-paced, agile environment Curiosity, humility, and a user-first mindset Bonus Points: Experience with Amplitude, Mixpanel, Segment, or similar tools for analyzing user engagement data Background in consumer tech, hardware/software products, or mobile-first experiences Experience using large language models (LLMs) for analysis or workflow acceleration The base salary range represents the low and high end of the anticipated salary range for this position based at our New York City headquarters. The actual base salary offered for this position will depend on numerous factors including, without limitation, experience and business objectives and if the location for the job changes. Our base salary is just one component of Peloton’s competitive total rewards strategy that also includes annual equity awards and an Employee Stock Purchase Plan as well as other region-specific health and welfare benefits. As an organization, one of our top priorities is to maintain the health and wellbeing for our employees and their family. To achieve this goal, we offer robust and comprehensive benefits including: Medical, dental and vision insurance Generous paid time off policy Short-term and long-term disability Access to mental health services 401k, tuition reimbursem ... (truncated, view full listing at source)
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