7+ years in risk, fraud analytics, trust and safety, or a similar investigative analytical role
Expert SQL. You can pursue a hypothesis across large behavioral datasets without supervision
Pattern recognition instinct. You can look at a cluster of accounts and articulate what they share and why it is unlikely to be coincidence
Experience building fraud detection rules or models, setting thresholds, evaluating precision and recall, monitoring performance, and adapting controls as risks evolve
Sound judgment about user impact. You understand that every control has a cost to legitimate users, and you can weigh the two
Comfort working alongside Compliance, with sound judgment and discretion in handling sensitive findings
Experience integrating internal and external datasets to generate actionable insights; experience partnering with vendors on experimentation, analytics, and implementation a plus
Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace
(Plus) Experience with on-chain analysis, wallet clustering, or blockchain forensics
(Plus) Experience with trade surveillance, market manipulation detection, or AML
(Plus) Statistical or machine learning background — anomaly detection, graph analysis, or clustering in Python or R
(Plus) Experience in fintech, crypto, prediction markets, or other data-intensive financial products