Senior Manager, Data Science - Product Analytics

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 Manager 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.

We are looking for a Sr. Manager, Product Analytics to spearhead the analytical initiatives designed to optimize our product strategy. This role is designed for to lead high impact projects, establish key frameworks, and lead a team of few analysts.

YOUR DAILY IMPACT AT PELOTON

• Collaborate with Product Management Org & Key Stakeholders to understand their business objectives, translate into proposed solutions (e.g., EDAs, new KPIs, BI, Data science) and socialize the proposals to ensure the stakeholder alignment & buy-in
• Be a thought partner and a consultant to the Performance Marketing & Product Marketing functions by proactively discovering strategic insights and analytical solutions that would drive growth in member engagement
• Understand and help improve Peloton’s product strategy and be able to deliver accurate, timely & high-quality analytics
• Be responsible for the development, oversight and presentation of insights & KPIs for business reviews and leadership updates
• Leverage industry best practices in optimizing the engagement strategies at Peloton through effective data & insights
• Support experimentation initiatives by partnering with the PMs for setting up effective A/B or multivariate tests, executing post-experiment success measurement and statistical quantification
• Lead an engaged, successful team of product analysts and data scientists 
• Grow and mentor the talent on the team, both technically & strategically on industry best practices such as statistical modeling, exploratory data analysis and experimentation analytics
• Establish a culture of high performance and motivate the team to raise the existing bar
• Partner with the centralized data platform team to build the required semantic data layers for effective analytical reporting & dashboards
• Partner with the Product Leadership to develop new KPIs & own the metrics scorecard for the Product Org

YOU BRING TO PELOTON

• BA/BS degree, preferably in a technical field
• 8+ years of experience in data science and statistics in product-led companies, preferably with significant experience in customer engagement strategies
• 3+ years of experience building, managing and leading analytics / data science teams
• Experience with Infrastructure and Tooling
• High proficiency in Python, SQL, and other data science tools
• Experience with self-service analytics tools (e.g., Google Analytics, Amplitude, Optimizely) and Data Visualization tools (e.g., Looker, Tableau, PowerBI)
• Strong interest in working with the latest AI-based tools and technologies, self-starter and promoter of adopting AI for problem solving & workflow automations 
• Strong quantitative skills & experience utilizing analytical techniques for Product Engagement & Marketing effectiveness 
• Experience with statistical analysis for A/B or multivariate tests
• Experience establishing data governance, ethics, and quality
• Excellent communication and collaboration skills: Role involves building positive relationships and communicating complex concepts effectively across the Product & Marketing organization
• Proactive, thoughtful and highly organized self-starter style: Thrives in ambiguity and solving open-ended problems without a clear right answer
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