Staff Data Analyst

ABOUT THE ROLE

We are seeking a Staff Data Analyst to serve as a strategic partner between our Global Operations & Technology organization and our Enterprise Data team. This role will be the voice of data for our Supply Chain and Global Member Support organizations. While serving as a hands‑on analyst and strategic partner, you will also have the opportunity to work within and learn from a larger data team.

• Partner with peer stakeholders, Directors, and VPs to define, build, and maintain a robust metric architecture. Consider North Star metrics, leading vs. lagging indicators, counter‑metrics, and operational guardrails. Create clear documentation and work to build consensus
• Lead a dedicated workstream that reviews key metrics weekly, reporting to the broader company the vital changes, trends, and strategic opportunities the metrics reveal. Perform root‑cause analysis on operational anomalies, separating true operational signals from noise, seasonality, or data pipeline breaks. Know when a scrappy analysis is sufficient and when a more nuanced approach is necessary
• Shape and deliver clear business narratives with appropriate nuance. Translate complex and ambiguous data into clear and concise recommendations
• Collaborate with cross‑functional partners on measurement strategy and data collection for pilot projects and new company‑wide initiatives
• Decompose ambiguous, high‑level business goals and strategic questions into structured, testable hypotheses and concrete analytical frameworks that drive decisions
• Partner with tech and operations teams to design, evaluate, and interpret operational experiments and process changes
• Become an in‑house expert on Peloton’s supply chain and member support data, while maintaining a broad awareness of other data domains across the company
• Evangelize the data our team has made available to the Global Ops and Tech teams. Ensure the organization is aware of what’s available and knows how to use it through dedicated documentation and training materials. Identify and act on gaps and opportunities in data adoption
• Develop strong partnerships with the technology stakeholders who own the operational systems driving Peloton’s supply chain. Think big‑picture as you document the broader data ecosystem, mapping out exactly how all of these disparate pieces and systems connect. Ensure we are in lockstep with Tech teams on planning and roadmap initiatives

• 7+ years of data analytics experience, with a proven track record operating at a senior level within a complex organization. Experience performing data extraction, cleaning, analysis and presentation for medium to large datasets. Practical knowledge of A/B testing and quasi‑experimental design (e.g., difference‑in‑differences)
• Advanced SQL proficiency and advanced experience with Looker (or similar enterprise BI tools). Highly fluent in spreadsheets (Excel/Google Sheets)
• Fluency analyzing data with Python and/or R
• Familiarity with dbt and modern analytics engineering principles
• Highly skilled in both written and verbal communication. You can convey complex technical concepts in straightforward ways to non‑technical executives and stakeholders
• You possess exceptional attention to detail and organizational skills. You can seamlessly context‑switch between high‑level architectural documentation and day‑to‑day triage, balancing multiple work streams and priorities
• You know how to establish trusted analytics and can confidently guide teams away from misleading metrics. You are comfortable with ambiguity and has a strategic mindset for solving complex, unstructured problems
• Experience working in deep partnership with cross‑functional teams—both technical and non‑technical
• The ideal candidate demonstrates the following:
  • You are highly analytical and think deeply about how complex systems talk to each other
  • You love asking questions, explaining your findings, and communicating insights in a way that empowers leadership to make data‑driven decisions
  • You are a scrappy, critical thinker who thrives on connecting the dots across complex systems
  • You know when to simplify a problem for clarity and when a…