Senior Data Scientist

This is a fully remote position, open to applicants in California.

📋 Description

• Develop and assess fraud models for various stages including onboarding, login, account modifications, and money transactions.

• Identify risks such as account takeover, scams, money mules, as well as stolen and synthetic identities.

• Analyze third-party risk indicators and facilitate the transition from vendor models to Circle models, progressing from shadow mode to production.

• Establish label taxonomy and data requirements in collaboration with Fraud Operations and Risk Engineering.

• Create holdout and exploration sampling strategies to evaluate false negatives and the wrongful blocking of legitimate customers.

• Monitor fraud rates, dispute rates, fraud loss rates, and precision across different customer segments.

• Assist in setting thresholds in line with an agreed-upon loss budget.

• Collaborate with Fraud Strategy to adjust thresholds and rules, as well as respond to emerging threats.

• Conduct backtesting, monitor model drift, and retrain models on Circle’s fraud platform.

• Contribute to the development of AI agent workflows for transaction reviews, fraud-ring analysis, and rule formulation.

• Assess the accuracy of AI agent workflows against human evaluations.

• Work alongside Fraud Strategy, Fraud Operations, Risk Engineering, and Compliance teams.

⛳️ Requirements

• Minimum of 5 years of experience in data science or applied machine learning focused on fraud, risk, or financial crime.

• Proficient in advanced Python and SQL.

• Familiarity with XGBoost, LightGBM, or similar frameworks.

• Experience in building models with sparse, delayed, or biased labels, including cold start, reject inference, and chargeback lag scenarios.

• Strong statistical knowledge including anomaly detection, graph or network methodologies, experimentation, and threshold optimization.

• Proven track record of taking models to production and overseeing their performance.

• Excellent communication skills to engage with both technical and non-technical stakeholders.

• Ability to navigate through ambiguity and work with limited historical data.

• Preferred: experience in fintech, payments, crypto, or card fraud, including chargebacks and disputes.

• Preferred: background in device intelligence, behavioral signals, or consortium data.

• Preferred: knowledge of blockchain analytics, anti-money laundering (AML), and know your customer (KYC) regulations.

• Preferred: experience in evaluating large language models or agent-based review workflows.

🏝️ Benefits

• Flexible work environment.

• Inclusive workplace culture.

• Equal opportunity employment policy.

• Interview accommodations or assistance available for candidates with disabilities.