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Data Scientist with expertise in fraud and risk to detect and prevent these threats to our community.
Job Responsibility:
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
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
What we offer:
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