Staff Data Analyst

Peloton Peloton · Consumer · Headquarters, NY · Data Analytics

Peloton is seeking a Staff Data Analyst to partner with Global Operations & Technology and Enterprise Data teams, focusing on Supply Chain and Global Member Support. The role involves defining and maintaining metric architecture, leading metric reviews, performing root-cause analysis, shaping business narratives, and collaborating on measurement strategies for new initiatives. The analyst will also design and evaluate operational experiments, become an expert in supply chain and member support data, and evangelize data availability. Key responsibilities include partnering with tech teams on system design and roadmap initiatives.

What you'd actually do

  1. 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
  2. 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
  3. Shape and deliver clear business narratives with appropriate nuance. Translate complex and ambiguous data into clear and concise recommendations
  4. Collaborate with cross-functional partners on measurement strategy and data collection for pilot projects and new company-wide initiatives
  5. Decompose ambiguous, high-level business goals and strategic questions into structured, testable hypotheses and concrete analytical frameworks that drive decisions

Skills

Required

  • 7+ years of data analytics experience
  • senior level experience in a complex organization
  • data extraction, cleaning, analysis and presentation for medium to large datasets
  • A/B testing and quasi-experimental design
  • Advanced SQL proficiency
  • 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
  • Exceptional attention to detail and organizational skills
  • Ability to context-switch between high-level architectural documentation and day-to-day triage
  • Ability to balance multiple workstreams and priorities
  • Ability to establish trusted analytics and guide teams away from misleading metrics
  • Comfortable with ambiguity
  • Strategic mindset for solving complex, unstructured problems
  • Experience working in deep partnership with cross-functional teams (technical and non-technical)

Nice to have

  • Experience automating routine tasks with AI
  • Start-up experience
  • Fluency in supply chain concepts and data

What the JD emphasized

  • advanced SQL proficiency
  • advanced experience with Looker
  • Fluency analyzing data with Python and/or R
  • Familiarity with dbt and modern analytics engineering principles
  • Highly skilled in both written and verbal communication
  • exceptional attention to detail and organizational skills
  • comfortable with ambiguity
  • strategic mindset for solving complex, unstructured problems
  • Experience working in deep partnership with cross-functional teams