Senior Data Analyst

Description

ABOUT the company

The company is a destination for builders, creators, innovators, and operators who want to come together and challenge the status quo. Our mission is simple: make really high quality essentials for really low prices, fairly and sustainably. We deliver on that mission through a unique manufacturer-to-consumer (M2C) model eliminating the layers of traditional retail that add cost and result in consumers paying more than they need to. We find, build relationships with, and work directly with the manufacturing partners behind some of the world’s finest products. From there, our teams design smart, efficient operational processes and build and deploy proprietary technology, AI, and analytics to help us scale fast.

What began with a small assortment of elevated basics has quickly grown into a cross-category brand spanning apparel, accessories, home goods, and more. Today, tens of millions of people across a growing number of countries come – and return – to the company because they trust us to deliver.

OUR CULTURE

The company is a culture built for builders by builders. Our way of working starts with a blank sheet of paper. We question conventional thinking, use technology and data to uncover new opportunities, and move quickly to turn ideas into reality. We aren’t interested in replicating how others do retail. We’re building a better way – at a speed and scale unlike anything that’s been done before.

We dream big and chase the hard problems others shy away from. Rejecting long-held assumptions is part of our company's DNA. Where conventional wisdom says you have to choose – soft or durable, speed or rigor, quality or price – we ask why that trade-off has to exist in the first place.

Our pace is fast and the bar is high because our customers expect a lot from us and we refuse to let them down. We believe the best results come from challenging ourselves, learning from one another, and building on each other's strengths.

Here, responsibility is not determined by role, tenure, or seniority. Every team member - no matter their level - has the opportunity to drive our business and shape our trajectory.

If you’re someone who likes to imagine new possibilities and build better systems rather than plug-in to outdated ones, the company is the place for you.

Responsibilities

• We're seeking a Senior Data Analyst to join our Storefront team, partnering across cart, checkout, post-purchase (returns & exchanges), and accounts to quantify what's working, what's broken, and what to build next. This role sits at the center of a live, high-velocity storefront: millions of customer sessions, real-time inventory and pricing signals, and decisions that need rigor and speed in equal measure. You'll build statistical models (causal inference, incrementality testing, funnel diagnostics) that separate signal from noise, design and run a disciplined experimentation program, and partner directly with Product, Engineering, and Design to prioritize the highest-impact opportunities across the post-cart customer journey.
• You are a true individual-contributor “super IC” — deeply technical, hands-on with Python and SQL every day, and fluent in the statistics that make an analysis trustworthy rather than just directional. You're excited by the newest AI tools and use them to move faster: LLM-assisted exploratory analysis, agentic coding for pipeline work, automated anomaly detection and insight generation. You have grit — you push through messy data, ambiguous asks, and legacy instrumentation to ship something correct, then iterate. You thrive with autonomy in a fast-moving environment where you set your own standards for rigor and communicate findings with clarity and confidence to stakeholders at every level.
• 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.

Requirements

• 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.
• All posted ranges are reflective of base salary and may vary depending upon experience level and location. Bonus and equity may also be provided for eligible roles.

Conditions

$150,000 - $200,000 USD

WHY the company?

Joining the company means being part of a mission-driven team reshaping retail. You will work alongside talented colleagues, tackle meaningful challenges, and contribute to building a more sustainable, accessible future for customers and partners alike.