The posting, in Riskified's own words
archived Nov 15, 2026About Us
Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Booking.com, Acer, Gucci, Lorna Jane, GoPro, and many more . We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day.
About the Role
Product Data Analysts at Riskified are a core part of the Product team. They work side by side with PMs and with our engineering, data science, design, growth, marketing, and operations teams to shape what we build and measure its impact. We are looking for people who solve complex problems with varied skills, and who learn and adjust quickly as the company and our product platform continue to expand. Our philosophy centers on end-to-end ownership: every team member is empowered and accountable. We hold ourselves to high standards, have ambitious goals, and are not afraid of trying new things. Riskified helps leading global merchants reduce fraud and chargeback losses. We are looking for a Product Data Analyst to take our chargeback analytics to the next level, in a deep, high-impact role. You’ll join the Product team and work closely with PMs, R&D, Data Science, Operations and Sales.
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What You'll Be Doing
Own performance analytics for our chargeback products. Go deep on what drives chargeback outcomes, and turn insights into product improvements. Design and analyze experiments to improve product performance. Partner with Data Science on predictive models. Give Sales and Account Management data-backed insights to show merchants the value we deliver. Track product health and adoption, and build it so it runs automatically. Present findings to product and business leadership.