About the roleAs Circle expands the customers and payment methods it serves, our fraud exposure grows and changes. We rely on conservative limits and third-party models today, and we are building our own.
As a Senior Data Scientist on Fraud Analytics, you will own the prediction side of our fraud loop. You will turn labels into features and models, measure their accuracy, and shift Circle from vendor scores to in-house models. You will work with Fraud Strategy, Fraud Operations, Risk Engineering, and Compliance.
What you'll do- Build and evaluate fraud models for onboarding, login, account changes, and money movement. Target risks include account takeover, scams, money mules, and stolen and synthetic identity.
- Evaluate third-party risk signals and design the path from vendor models to Circle models, from shadow mode to production.
- Define the label taxonomy and data requirements with Fraud Operations and Risk Engineering, so every event, decision, and outcome becomes training data. This includes the fraud we miss.
- Design holdout and exploration sampling to measure false negatives and the rate at which we wrongly block good customers.
- Track fraud rate, dispute rate, fraud loss rate, and precision across customer segments. Help set thresholds against an agreed loss budget.
- Work with Fraud Strategy to tune thresholds and rules and respond to emerging attacks.
- Backtest, monitor drift, and retrain models on Circle's fraud platform.
- Help build AI agent workflows for transaction review, fraud-ring analysis, and rule drafting, and evaluate their accuracy against human labels.
Core Requirements- 5+ years in data science or applied ML on fraud, risk, or financial crime
- Advanced Python and SQL, and experience with XGBoost, LightGBM, or similar
- Experience building models with sparse, delayed, or biased labels, including cold start, reject inference, and chargeback lag
- Strong statistics: anomaly detection, graph or network methods, experimentation, and threshold optimization
- Experience taking models to production and monitoring them
- Clear communication with technical and non-technical partners
- Comfort working through ambiguity and limited historical data
Preferred Requirements- Fintech, payments, crypto, or card fraud experience, including chargebacks and disputes
- Experience with device intelligence, behavioral signals, or consortium data
- Familiarity with blockchain analytics, AML, and KYC
- Experience evaluating LLM or agent-based review workflows
Circle is on a mission to create an inclusive financial future, with transparency at our core. We consider a wide variety of elements when crafting our compensation ranges and total compensation packages.
Starting pay is determined by various factors, including but not limited to: relevant experience, skill set, qualifications, and other business and organizational needs. Please note that compensation ranges may differ for candidates in other locations.
Base Pay Range: $152,500 - $205,000
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