About the job
Be Part of the E-Commerce Revolution with Whatnot!
Whatnot stands as the largest live shopping platform across North America and Europe, where you can buy, sell, and explore the products you love. We're transforming the e-commerce landscape by integrating community, shopping, and entertainment into a unique experience tailored just for you. As a part of our remote co-located team, we thrive on innovation while being grounded in our core values. With offices in the US, UK, Germany, Ireland, and Poland, we are collaboratively crafting the future of online marketplaces.
From fashion and beauty to electronics and collectibles such as trading cards, comic books, and even live plants, our live auctions cater to diverse interests.
And this is just the beginning! As one of the fastest-growing marketplaces, we seek adventurous, innovative problem solvers across all sectors. Stay updated with Whatnot through our news and engineering blogs, and join us in empowering individuals to transform their passions into thriving businesses while fostering connections through commerce.
Your Role
As Whatnot continues to expand rapidly, data plays a crucial role in shaping our product strategy and crafting exceptional, high-performance experiences for both buyers and sellers. We are in search of a Product Data Scientist who will collaborate closely with Product, Engineering, Design, and Operations teams to generate insights, drive experimentation, and influence decision-making throughout the organization.
In this pivotal role, you will:
Discover Insights & Influence Product Strategy
Define and manage the KPIs that gauge product health, user engagement, and marketplace performance.
Examine user behavior, product usage patterns, and marketplace trends to pinpoint opportunities and guide product priorities.
Convert complex data into practical recommendations for product and leadership teams.
Foster Experimentation & Evaluation
Collaborate with product managers and engineers to design, execute, and assess A/B tests and feature launches.
Create frameworks for causal inference, impact assessment, and long-term product evaluation.
Develop scalable methodologies for data analysis and reporting.

