Staff Product Data Scientist, Risk and Payments

Owner
San Francisco$200k – $240kPosted 1 April 2026

Job Description

Staff Product Data Scientist, Risk and Payments About Owner.com http://owner.com/ Owner is the AI growth system for local restaurants. Our AI continuously improves SEO, marketing, and online ordering to grow first-party orders. Unlike other companies that force small business owners to master their software to drive sales, Owner gives them a proven system run by experts. Owner is like having an army of engineers and marketers on your side, just like the big chains. Our vision We’re starting by helping independent restaurants succeed online. But it’s not just restaurants that need our help. Most local businesses are struggling with these same problems. Huge technology corporations are taking their customers, bleeding their profits, and making it hard for them to survive. Once we nail the solution for restaurants – we’ll scale it into every other local business type. In the future we envision, tens of millions of local business owners will use our technology to succeed in the digital age. Read our Series C memo here → https://www.owner.com/c Our traction Since 2020, we've generated tens of millions in revenue and processed over half a billion dollars of online orders. 1 in 5 Americans have used an Owner.com http://Owner.com website. More importantly, we’ve helped over 20,000 restaurant owners, and saved them nearly $200 million in fees. Our team Our team is now in the low hundreds. We’ve got top talent from the most successful companies in SMB software, including: Shopify, HubSpot, DoorDash, ServiceTitan, Rappi, Faire and Stripe. We’ll be scaling even faster in 2026 to keep pace with our customer growth. Where we work Owner is a remote-first, global company headquartered in San Francisco, with a sales hub in Toronto. For a few of our roles we prioritize in-person collaboration at one of our office locations. Most of our teammates are distributed throughout the globe. Please review the role description and discuss with your recruiter for more details on location. Why we’re looking for you We’re building an effective, impactful Product Analytics function at Owner.com http://owner.com/. As a Risk & Payments Data Scientist, you will play a pivotal role in shaping the product roadmap through close collaboration with Product Managers to establish proper metrics and impact sizing. You will drive experimentation initiatives and manage the testing framework. You will be instrumental in designing and implementing KPIs for our payments product squad, identifying gaps and potential opportunities that will help grow the business. The best candidates will not just provide insights to the EPD (Engineering & Product) org, but be a strategic driver, identifying gaps/opportunities in the money & risk area, building internal alignment around them, and creating meaning business impact. We’re migrating from Stripe Standard to Custom Connect / Adyen for Platforms, which means we’ll own far more of the risk surface: merchant onboarding/underwriting, fraud detection, dispute mitigation, reserves, and payout risk. As a Risk Data Scientist you will be building the models, signals, and decisioning that protect our merchants and our P&L—while keeping conversion high and friction low. For this particular role we are focused on candidates located in the San Francisco Bay Area. We are a remote-first company with a home base in SF, where our team comes together for periodic in-person collaboration (most local teammates opt to come in on Tuesdays/Thursdays). For more details chat with your recruiter! The impact you will have - Payments modeling: - Cut losses without killing conversion: Ship ML models that reduce fraud/chargebacks and credit losses while maintaining checkout auth rates and onboarding pass-through. - Accelerate safe growth: Create merchant risk scores and dynamic controls (e.g., reserves/holdbacks, payout delays) that scale to 10k+ restaurants. - Give Ops superpowers: Build signals, alerts, and tools that let our Paymen ... (truncated, view full listing at source)
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