Data Scientist, Risk & Fraud
Indexed description
馃殌 Join the Future of Commerce with Whatnot! Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce. 馃捇聽Role聽 In order to continue this growth, it鈥檚 important that Whatnot remains a safe and trusted space to interact and transact. We鈥檙e looking for a Data Scientist with expertise in fraud and risk to detect and prevent these threats to our community. You will: 馃攳Generate Insights & Shape Direction Translate complex data into actionable recommendations for the Fraud engineering and operations teams. Define and own the KPIs that measure the cost of fraud, strategies to prevent it, and impact to users and marketplace performance. Analyze the effectiveness of existing methods and partner with product and machine learning engineers to develop better anti-fraud practices. 馃ИDrive Experimentation & Measurement Partner with product managers, engineers, and operations teams to design, implement, and evaluate feature rollouts to combat bad actors on the platform. Define and own the experimentation playbook for Fraud at Whatnot. Develop frameworks for causal inference and impact measurement of efforts that are not well-suited to A/B testing. Ensure Whatnot鈥檚 internal KPIs treat fraudulent actors appropriately in measurement outside of fraud domains. 馃洜 Build Data Products & Tools Use our modern data stack to build dashboards, data pipelines, and self-serve tools that empower teams across Whatnot. Partner with engineers to improve data accessibility, ensure data quality, and support instrumentation for new product and platform enhancements. 馃Lead Cross-Functional Collaboration Advocate for data-driven decision-making and foster a culture of measurement across the trust & risk organization. Communicate insights clearly to both technical and non-technical audiences, influencing roadmaps and strategic decisions. Bring data support to company-critical investigations to quantify and thwart bad actor tactics, and help generalize outputs to create longer-term protections for different fraud vectors. Serve as a thought leader to Trust & Risk leadership, shaping how we build, launch, and iterate on fraud strategy across the platform. US聽Based: We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs. 馃憢聽You聽 People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it. As our next Data Scientist, Risk & Fraud, you bring: 馃帗Experience & Expertise 5+ years of experience in the Data field, and 3+ years of experience in Data Analytics & Science supporting anti-fraud, risk, trust & safety, or integrity problems. Bachelor鈥檚 degree in Computer Science, Economics, Statistics, Cybersecurity, or a related field, or equivalent work experience. Industry experience with proven ability to apply scientific methods to solve real-world problems on large scale data. 馃Technical Skills Advanced SQL skills and experience with modern data warehouses (Snowflake, BigQuery, Redshift) and tools like Spark or DBT. Proficiency with Python or R for data analysis, modeling, and experimentation. Experience designing and analyzing A/B tests and understanding causal inference techniques. Strong data visualization skills and familiarity with BI tools for building interactive dashboards. 馃棧锔廋ollaboration & Leadership Ability to communicate complex ideas clearly, concisely, and impactfully across diverse stakeholders. Experience leading cross-functional projects and influencing trust & risk strategy with data. Comfortable working in fast-paced, ambiguous environments with a high degree of ownership. 馃挵Compensation For聽Full-Time聽(Salary)聽US based聽applicants:聽 $185,000/year聽to聽$240,000/year聽+聽benefits聽+聽equity. The聽salary聽range聽may聽be聽inclusive聽of聽several聽levels聽that聽would聽be聽applicable聽to聽the聽position.聽Final聽salary聽will聽be聽based聽on聽a聽number聽of聽factors聽including,聽level,聽relevant聽prior聽experience,聽skills,聽and聽expertise.聽This聽range聽is聽only聽inclusive聽of聽base聽salary,聽not聽benefits聽(more聽details聽below)聽or聽equity. 馃巵聽Benefits聽 Flexible聽Time聽off聽Policy聽and聽Company-wide聽Holidays聽(including聽a聽spring聽and聽winter聽break) Health聽Insurance聽options聽including聽Medical,聽Dental,聽Vision Work聽From聽Home聽Support Home聽office聽setup聽allowance Monthly聽allowance聽for聽cell聽phone聽and聽internet Care聽benefits Monthly聽allowance聽for聽wellness Annual聽allowance聽towards聽Childcare Lifetime聽benefit聽for聽family聽planning,聽such聽as聽adoption聽or聽fertility聽expenses Retirement;聽401k聽offering聽for聽Traditional聽and聽Roth聽accounts聽in聽the聽US聽(employer聽match聽up聽to聽4%聽of聽base聽salary)聽and聽Pension聽plans聽internationally Monthly allowance to dogfood the app All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!). Parental聽Leave 16聽weeks聽of聽paid聽parental聽leave聽+聽one聽month聽gradual聽return聽to聽work聽*company聽leave聽allowances聽run聽concurrently聽with聽country聽leave聽requirements聽which聽take聽precedence. 1212 馃挍 EOE Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.
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