Senior Data Scientist

Senior Data Scientist On Fraud AnalyticsCircle is committed to visibility and stability in everything we do. As we grow as an organization, we're expanding into some of the world's strongest jurisdictions. Speed and efficiency are motivators for our success and our employees live by our company values: High Integrity, Future Forward, Multistakeholder, Mindful, and Driven by Excellence. We have built a flexible work environment where new ideas are encouraged and everyone is a stakeholder.As 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 crimeAdvanced Python and SQL, and experience with XGBoost, LightGBM, or similarExperience building models with sparse, delayed, or biased labels, including cold start, reject inference, and chargeback lagStrong statistics: anomaly detection, graph or network methods, experimentation, and threshold optimizationExperience taking models to production and monitoring themClear communication with technical and non-technical partnersComfort working through ambiguity and limited historical dataPreferred Requirements:Fintech, payments, crypto, or card fraud experience, including chargebacks and disputesExperience with device intelligence, behavioral signals, or consortium dataFamiliarity with blockchain analytics, AML, and KYCExperience evaluating LLM or agent-based review workflowsBase Pay Range: $152,500 - $205,000We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status, or any other protected status required by the laws in the locations where we hire. Additionally, Circle participates in the E-Verify Program in certain locations, as required by law. Should you require accommodations or assistance in our interview process because of a disability, please reach out to View email address on click.appcast.io for support. We respect your privacy and will connect with you separately from our interview process to accommodate your needs.