Senior Fraud ML Scientist - Fintech Payments

Learndevs; United States; On-site; USD 153,000 - 205,000; Full time

Job summary

Circle is expanding its fraud analytics team in the United States. The Senior Data Scientist will own the prediction side of the fraud loop, turning labels into features and models, and migrating from vendor scores to in‑house solutions.

You will collaborate with Fraud Strategy, Operations, Risk Engineering, and Compliance to design scalable detection across onboarding, login, and money movement. You will build and evaluate models, define label taxonomies, and monitor drift and performance.

Qualifications

• 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.

Responsibilities

• 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 wrongfully 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.

Skills

Data science

Python

SQL

XGBoost/LightGBM

Statistics

Model production

Communication

Job description

Circle is expanding its fraud analytics team in the United States. The Senior Data Scientist will own the prediction side of the fraud loop, turning labels into features and models, and migrating from vendor scores to in‑house solutions.

You will collaborate with Fraud Strategy, Operations, Risk Engineering, and Compliance to design scalable detection across onboarding, login, and money movement. You will build and evaluate models, define label taxonomies, and monitor drift and performance.