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Senior Data Analyst, Storefront

Quince· Data Science
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Palo Alto, CA$150k - $200kFull-timePosted 1w ago

About the role

Senior Data Analyst to join the Storefront team, partnering across cart, checkout, post-purchase and accounts to quantify what’s working, what’s broken, and what to build next. Centered on a live, high-velocity storefront with real-time signals; build statistical models, run disciplined experiments, and translate findings into product requirements with Product, Engineering, and Design.

Responsibilities

  • Own end-to-end analytics and data science support for cart, checkout, post-purchase (returns & exchanges), and accounts — from problem framing to statistical modeling to shipped recommendation.
  • Design and run experiments (A/B tests, holdouts) across these surfaces, including sizing, guardrail metrics, variance reduction, and rigorous post-test readouts.
  • Apply causal inference methods (e.g., diff-in-diff, synthetic control, incrementality testing) when randomized testing isn't feasible, especially for returns/exchanges policy and account-experience changes.
  • Drive funnel diagnostics and root-cause analysis across cart abandonment, checkout drop-off, return/exchange friction, and account engagement — segmented by device, traffic source, geo, and cohort.
  • Partner directly with Product, Engineering, and Design on these teams to prioritize hypotheses, size opportunities, and translate findings into clear product requirements and trade-offs.
  • Build and maintain source-of-truth metrics and self-serve dashboards for cart/checkout/post-purchase/accounts KPIs; flag regressions and anomalies proactively.
  • Write and maintain the SQL and Python pipelines behind your own analyses; partner with Data Engineering on event instrumentation, validation, and data quality.
  • Adopt and champion AI/LLM-powered workflows — from analysis acceleration to automated anomaly narratives — to raise the team's analytical throughput.
  • Communicate insights with clear, evidence-based storytelling to cross-functional stakeholders and leadership; run post-mortems and document learnings so they compound.

Qualifications

  • Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Economics, Math, or a related quantitative field.
  • 5+ years of experience as a data scientist or quantitative analyst, ideally on a consumer-facing product, e-commerce, or marketplace team.
  • Deep hands-on expertise in Python and SQL — you write and debug both yourself, daily, not just direct others to.
  • Strong grounding in statistics and experimentation: hypothesis testing, regression, experiment design, and causal inference methods (e.g., diff-in-diff, propensity matching, incrementality/geo-lift testing).
  • Track record of scoping and running experiments end-to-end, from design through analysis to a decision-ready readout.
  • Experience with BI/visualization tools (e.g., Looker, Mixpanel) and comfort building self-serve dashboards that stakeholders actually use.
  • AI-forward: you actively use LLMs and AI-assisted tooling in your own analytical and engineering workflow, and you stay current on what's newly possible.
  • Excellent written and verbal communication; able to translate ambiguous, cross-functional problems (cart, checkout, returns, accounts) into a clear analytical plan and a clear recommendation.
  • Grit and ownership: comfortable with ambiguity, messy data, and a fast-moving startup environment with limited process.

Skills

Required:PythonSQLStatistics and experimental designA/B testing and experimentationBI/visualization toolsCommunication
Nice to have:AI tools / LLMs in analytics
Last updated Oct 14, 2026. Interested? Apply on the company site.
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About Quince

High Quality Essentials, Radically Low Prices

Quince brings luxury products like Mongolian Cashmere, Italian Leather, Turkish Cotton and Washable Silk to everyone at radically low prices. Shop premium essentials with no middleman.

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