Data Scientist, Product Analytics

Role Overview

As a Product Data Scientist (Product Analytics) at Whatnot, you’ll partner with Product, Engineering, Design, and Operations to drive insights, experimentation, and data-informed decision-making.

Responsibilities

• Define and own KPIs for product health, user engagement, and marketplace performance.
• Analyze user behavior and product usage to identify opportunities and inform product priorities.
• Translate complex analyses into actionable recommendations for product and leadership.
• Design, implement, and evaluate A/B tests and feature rollouts with PMs and engineers.
• Develop causal inference and impact measurement frameworks and support long-term product evaluation.
• Build scalable methods to assess feature performance and guide iteration.
• Use Whatnot’s modern data stack to create dashboards, data pipelines, and self-serve tools.
• Partner with engineering to improve data accessibility, data quality, and instrumentation for new features.
• Advocate for data-driven decisions and communicate findings to both technical and non-technical audiences.

Requirements

• 3+ years of experience in Data Science/Decision Science/Analytics in a product-focused environment.
• Bachelor’s degree in Computer Science, Economics, Statistics, or related quantitative field (or equivalent experience).
• Proven ability to apply statistical/analytical methods to product problems.

Technical Skills

• Advanced SQL and experience with modern data warehouses: Snowflake, BigQuery, Redshift.
• Experience with Spark and/or dbt (DBT).
• Proficiency in Python or R for analysis, modeling, and experimentation.
• Experience designing and analyzing A/B tests.

Nice-to-haves / Additional Notes

• Must be US-based and live within commuting distance of one of: New York, Seattle, Los Angeles, or San Francisco. Work can be flexible between home and global hubs with value placed on in-person time.