Staff Product Manager, Radar - Fraud and Abuse Prevention

The shape of it

In the posting’s own words

Radar helps businesses prevent fraud and abuse without getting in the way of legitimate customers. We combine machine learning powered by Stripe’s global network with intuitive dashboard experiences and developer APIs, to give our users comprehensive controls and insights to protect their business against threats ranging from payment fraud and card testing to bot and free trial abuse.

What it asks for · 10

• 10+ years of Product Management experience
• Highly analytical, with a rigorous approach to quantitative and qualitative evidence. You’re comfortable digging into data, writing SQL when needed, and defining metrics that connect product decisions to user outcomes.
• Scrappy and resourceful, with experience taking products from zero to one. You find ways to test ideas quickly, learn from real users, and turn early solutions into products that scale.
• Strong commercial and business acumen. You understand how customer problems translate into willingness to pay, adoption, and durable business value.
• Proven cross-functional leadership, including experience partnering with B2B sales teams on customer discovery, product positioning, and adoption.
• Experience shipping Dashboard and API products, with empathy for both end users and developers and an understanding of their different workflows.
• Comfort with substantial ambiguity. You can set direction with incomplete information, make thoughtful trade-offs, and adapt as new evidence emerges.
• Technical fluency to go deep with engineering and data teams on complex systems, understand constraints, and evaluate alternative approaches.
• Strong written and verbal communication skills, with a talent for distilling complex customer problems into precise, actionable framing.
• An ownership mindset and a high bar for product quality. You do what it takes to solve user problems and care deeply about the details of the experience.

Also a plus

• Experience building fraud prevention, risk, security, or ML powered products.
• Experience developing machine learning powered products and evaluating trade-offs between detection effectiveness and customer friction.
• Experience building tools for fraud analysts or risk teams, or developer products that support real-time decisions.
• Software engineering, data science, or similar technical experience.

What the job covers

• Develop a deep understanding of the fraud and abuse landscape.
• Investigate emerging attacks with customers, assess their financial and operational impact, and distinguish isolated incidents from opportunities to build broadly useful defenses.
• Translate findings into a product strategy and roadmap, prioritizing the defenses that deliver the greatest customer and business impact.
• Partner with engineering, data science, and design to explore signals, shape solutions, and rapidly turn effective defenses into scalable, reliable products.
• Set the pace for the team by scoping the product thoughtfully, prioritizing ruthlessly, and executing with high rigor.
• Work with sales, marketing, and customer-facing teams to validate demand, coordinate launches, and help customers adopt and maximize the value they get from new capabilities.
• Own product performance, user experience, and business metrics to guide iteration and communicate progress.

Tools and skills named

Words the posting leans on

• product18×
• experience12×
• customers11×
• fraud9×
• user7×
• business6×
• abuse5×
• defenses4×
• developer4×
• problems4×
• requirements4×
• attacks3×
• businesses3×
• capabilities3×
• complex3×
• data science3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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