We’re building the future of ecommerce, bringing together community, shopping and entertainment. We are committed to our values, and as a remote-first team, we operate out of hubs within the US, Canada, UK, Ireland, and Germany today.

We’re innovating in the quick-paced world of live auctions in categories including sports, fashion, video games, and streetwear. The platform couples rigorous seller vetting with a focus on community to create a welcoming space for buyers and sellers to share their passions with others.

We’re looking for a Data Scientist with expertise in fraud and risk to detect and prevent these threats to our community. Create rules and systems to enhance the full lifecycle of risk and fraud measurement. Define and own the experimentation playbook for Fraud at Whatnot.

Partner closely across the business to find improvements/opportunities and influence decisions using data science methodologies and tools.

Build actionable KPIs, create production-quality dashboards and notebooks to convey insights.

Define and advance best practices to enable system-level solutions to reduce fraud and payment risk.

Analyze the effectiveness of existing methods and partner with Machine Learning and Trust & Safety teams to develop better anti-fraud practices.

Inform the engineering, operations, and machine learning roadmaps through analysis of marketplace, user behavior, and product trends.

We are looking for intellectually curious, highly motivated individuals to be foundational members of our Data team! You will partner with our Engineering, Product, and Operations teams to systematically detect, measure, and action against fraud and other threats to Whatnot’s platform.

The ideal candidate will be adept in navigating the data stack and able to support initiatives in all facets from analytics/data engineering and product analytics to machine learning, ideally with previous experience within fraud-adjacent domains.





In addition to 5+ years of experience in the Data field, you should have:

3+ years of experience in Data Analytics & Science supporting anti-fraud, risk, trust & safety, or integrity problems.

Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators

Bachelor’s degree in Computer Science, Economics, Statistics, 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

Comfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto/Trino, Athena, Spark, DBT

Expert in using SQL for data analysis, reporting, and dashboarding

Experience with a scripting language such as Python or R

Aptitude and experience in applied statistical modeling and machine learning techniques

Firm grasp of visualization tools, interactive and self-serving, such as business intelligence and notebooks

This range is only inclusive of base salary, not benefits (more details below) or equity in the form of stock options.

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

$1,000 home office setup allowance

$150 monthly allowance for cell phone and internet

450 monthly allowance on food

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

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.

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.

📌 Data Scientist, Risk & Fraud (Toronto)
🏢 Whatnot
📍 Toronto