Data Scientist, Risk & Fraud at whatnot

This role is ideal for a mid-to-senior level Data Scientist with significant experience in trust, safety, or fraud prevention within a marketplace or e-commerce

Work type: onsite

Location: San Francisco, CA | New York, NY | Los Angeles, CA | Seattle, WA

Salary: $185,000 – $240,000/yr

Type: Full-time

Summary

This role is ideal for a mid-to-senior level Data Scientist with significant experience in trust, safety, or fraud prevention within a marketplace or e-commerce environment. You should have at least 5 years of experience in data science, with a proven track record of using SQL and Python to dismantle "bad actor" tactics and build automated risk frameworks. The compensation is highly competitive ($185k–$240k base) and includes equity and comprehensive benefits like 16 weeks of parental leave and home office stipends. While the team is "remote co-located," you must live within commuting distance of their hubs in SF, NY, LA, or Seattle to participate in in-person strategy and problem-solving sessions. **You might be a good fit if you...** * Have 3+ years of specific experience in anti-fraud, risk, or integrity analytics. * Are proficient with the modern data stack (Snowflake, dbt, Spark) and causal inference techniques beyond standard A/B testing. * Enjoy a high-ownership environment where you act as both a technical builder and a strategic advisor to leadership. * Are excited about "dogfooding" a live shopping app as both a buyer and a seller.

Job Description

## 🚀 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](https://www.whatnot.com/careers) 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](https://a16z.com/marketplace-100/) and were recently named the [#1 Best Startup Employer in America](http://google.com/search?q=%231+forbes+startup+employer&oq=%231+forbes+startup+employer&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIGCAEQRRg9MgYIAhBFGD0yBggDEEUYQDIGCAQQRRhAMgYIBRBFGEDSAQg1NzM0ajBqMagCALACAA&sourceid=chrome&ie=UTF-8) by Forbes. Check out the latest Whatnot updates on our [news](https://blog.teamwhatnot.com/) and [engineering blogs](https://medium.com/whatnot-engineering) and join us as we enable anyone to turn their passion into a business and bring people together through commerce.

## 💻 Role

In order to continue this growth, it’s important that Whatnot remains a safe and trusted space to interact and transact. We’re looking for a Data Scientist with expertise in fraud and risk to detect and prevent these threats to our community. You will:

🔍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.

• 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’s internal KPIs treat fraudulent actors appropriately in measurement outside of fraud domains.

• 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.

• 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.

## 👋 You

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:

🎓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’s 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.

• 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.

• 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.

For Full-Time (Salary) US based applicants:$185,000/year to $240,000/year + benefits + equity.

The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.

## 🎁 Benefits

• Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)

• Health Insurance options including Medical, Dental, Vision

• Work From Home Support

• Home office setup allowance

• Monthly allowance for cell phone and internet

• Care benefits

• Monthly allowance for wellness

• Annual allowance towards Childcare

• Lifetime benefit for family planning, such as adoption or fertility expenses

• Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans 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 Leave

• 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.

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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