Responsibilities
- Generate insights and shape direction by translating 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.
Requirements
- 5+ years of experience in the Data field
- 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
Work Arrangement
Hybrid — New York, Seattle, Los Angeles, San Francisco
Additional Information
- All Whatnauts are expected to develop a deep understanding of our product.
- All employees are expected to use Whatnot as both a buyer and a seller as part of their job.
- 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
- 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.
