Data Scientist, Product Analytics

Base Pay Range

$/yr - $/yr

As Whatnot rapidly scales, data is central to shaping our product strategy and helping us build delightful, high-performing experiences for both buyers and sellers. We’re looking for a Product Data Scientist who will partner closely with Product, Engineering, Design, and Operations to drive insights, experimentation, and decision-making across the company.

• Define and own the KPIs that measure product health, user engagement, and marketplace performance.
• Analyze user behavior, product usage patterns, and marketplace dynamics to identify opportunities and inform product priorities.
• Translate complex data into actionable recommendations for product and leadership teams.

• Partner with product managers and engineers to design, implement, and evaluate A/B tests and feature rollouts.
• Develop frameworks for causal inference, impact measurement, and long-term product evaluation.
• Build scalable methodologies to understand feature performance and guide iteration.

• Use our modern data stack to build dashboards, data pipelines, and self-serve tools that empower teams across Whatnot.
• Partner with engineers to improve data accessibility, ensure data quality, and support instrumentation for new product features.

• Advocate for data-driven decision-making and foster a culture of measurement across the product organization.
• Communicate insights clearly to both technical and non-technical audiences, influencing roadmaps and strategic decisions.
• Serve as a thought partner to product leads, shaping how we build, launch, and iterate on experiences across the platform.

We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.

Curious about who thrives at Whatnot? We’ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here.

• 3+ years of experience in Data Science, Decision Science, or Analytics within a product-focused organization.
• A bachelor’s degree in Computer Science, Economics, Statistics, or a related quantitative field or equivalent experience.
• Proven experience applying statistical and analytical methods to real-world product problems.

• Advanced SQL skills and experience with modern data warehouses (Snowflake, Big Query, Redshift) and tools like Spark or DBT.
• Proficiency with Python or R for data analysis, modeling, and experimentation.
• Experience designing and analyzing A/B tests and understanding causal inference techniques.
• Strong data visualization skills and familiarity with BI tools for building interactive dashboards.

• Ability to communicate complex ideas clearly, concisely, and impactfully across diverse stakeholders.
• Experience leading cross-functional projects and influencing product strategy with data.
• Comfortable working in fast-paced, ambiguous environments with a high degree of ownership.

For full-time (salary) US based applicants: $175,000/year to $240,000/year + benefits + equity.

The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits or equity.

• Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)
• Health Insurance options including Medical, Dental, Vision
• Work From Home Support
• Home office setup allowance
• Monthly allowance for cell phone and internet
• Care benefits
• Monthly allowance for wellness
• Annual allowance towards Childcare
• Lifetime benefit for family planning, such as adoption or fertility expenses
• Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
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