About the job
Be Part of the E-Commerce Revolution with Whatnot!
Whatnot stands as the largest live shopping platform in North America and Europe, where users can buy, sell, and explore the items they cherish. We are transforming the e-commerce landscape by merging community, shopping, and entertainment into a unique marketplace tailored for you. As a remote co-located team, our culture thrives on innovation, firmly grounded in our core values. With operational hubs across the US, UK, Germany, Ireland, and Poland, we are collaboratively shaping the future of online marketplaces.
Whether it's fashion, beauty, electronics, or collectibles like trading cards and comic books, our live auctions cater to diverse interests.
And we’re just at the beginning! As one of the fastest-growing marketplaces, we seek audacious, innovative problem solvers across all departments. Stay updated with Whatnot’s latest developments through our news and engineering blogs, and join us in empowering individuals to transform their passions into businesses and connect communities through commerce.
Role Overview
As Whatnot continues its rapid expansion, data plays a pivotal role in influencing our product strategy and enhancing the user experience for both buyers and sellers. We are in search of a Product Data Scientist who will closely collaborate with Product, Engineering, Design, and Operations teams to extract insights, spearhead experimentation, and support data-driven decision-making across the organization.
In this position, you will:
Generate Insights & Shape Product Direction
Establish and take ownership of the KPIs that gauge product vitality, user engagement, and marketplace success.
Examine user behavior, product usage trends, and marketplace dynamics to pinpoint opportunities and guide product priorities.
Convert intricate data into actionable insights for product and leadership teams.
Drive Experimentation & Measurement
Collaborate with product managers and engineers to design, execute, and assess A/B tests and feature launches.
Create frameworks for causal inference, impact evaluation, and long-term product assessment.
Develop scalable methodologies for performance tracking and reporting.

