Senior Data Scientist / Analyst, Risk
The role investigates coordinated abuse and financial risk across a prediction-market platform, develops detection rules and monitoring, and partners with product and compliance on controls. It requires 7+ years in risk or fraud analytics, expert SQL, strong investigative judgment, and experience balancing false positives against missed abuse.
About the job
Responsibilities
- Investigate and quantify abuse across the funnel, including multi-accounting and fake signups, bonus and promotion farming, wash trading, collusion, and market manipulation.
- Build detection logic that separates genuine users from coordinated behavior using on-chain, device, and behavioral signals.
- Turn one-off investigations into monitoring, recurring reporting, and alerting that surfaces new patterns.
- Size the financial exposure of each abuse vector to prioritize controls based on actual cost.
- Partner with product on controls for onboarding, verification, bonus eligibility, and measure their impact on legitimate users.
- Support compliance with analysis for investigations, escalations, and regulatory reporting.
- Work with analytics engineers to promote detection logic into the modeled layer for reliable execution.
- Own documentation, including detection thresholds and rationale, so compliance and engineering teams can follow the logic independently.
Requirements
- 7+ years of experience in risk, fraud analytics, trust and safety, or a similar investigative analytical role.
- Expert SQL skills and the ability to investigate hypotheses across large behavioral datasets independently.
- Strong pattern-recognition ability, including identifying coordinated account behavior and explaining why it is unlikely to be coincidental.
- Experience building detection rules or models, with sound judgment around false positives and missed abuse.
- Ability to evaluate the impact of controls on legitimate users.
- Comfort working with compliance and handling sensitive findings appropriately.
- Ability to operate effectively in a fast-moving environment with frequently changing business logic.
Nice-to-Haves
- On-chain analysis, wallet clustering, or blockchain forensics.
- Trade surveillance, market manipulation detection, or AML experience.
- Statistical or machine learning experience, including anomaly detection, graph analysis, or clustering in Python or R.
- Experience in fintech, crypto, prediction markets, or other data-intensive financial products.
Compensation and Benefits
- Competitive salary and equity.
- Unlimited PTO.
- Full health, vision, and dental coverage.
- 401(k) match.
- Hardware setup including a new MacBook Pro, large display, and accessories.
Skills
SQL, Python, R, Anomaly Detection, Graph Analysis, Clustering, Blockchain Forensics, On-Chain Analysis, Wallet Clustering, Trade Surveillance, AML, Machine Learning, Data Modeling, Alerting, Fraud Analytics
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