Senior Data Scientist

Circle

. Build and evaluate fraud models for onboarding, login, account changes, and money movement .

Posted 10/16/2026full-timeRemote • California • United StatesSenior💰 $152,500 - $205,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and evaluating fraud models using advanced Python and SQL, with a strong focus on statistics and machine learning techniques for risk assessment in financial crime. Proficient in collaborating with cross-functional teams to optimize fraud detection strategies and ensure compliance with industry standards.

Highest-signal resume keywords

Advanced PythonSQLXGBoostLightGBMFraud Model Evaluation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceApplied Machine LearningAnomaly DetectionThreshold OptimizationModel MonitoringFraud Rate TrackingFalse Negative MeasurementChargeback AnalysisBehavioral Signals AnalysisLLM Evaluation

Soft Skills

Clear CommunicationComfort with Ambiguity

Tools & Technologies

Fraud PlatformAI Agent WorkflowsBlockchain Analytics

Industry Keywords

FintechPaymentsCryptoCard FraudAMLKYCVendor ModelsRisk EngineeringFraud OperationsDisputes

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Build and evaluate fraud models for onboarding, login, account changes, and money movement
Target risks including account takeover, scams, money mules, and stolen and synthetic identity
Evaluate third-party risk signals and design the transition from vendor models to Circle models, from shadow mode to production
Define label taxonomy and data requirements with Fraud Operations and Risk Engineering
Design holdout and exploration sampling to measure false negatives and wrongful blocking of 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
Evaluate AI agent workflow accuracy against human labels
Work with Fraud Strategy, Fraud Operations, Risk Engineering, and Compliance

Requirements

What you’ll need

5+ years in data science or applied ML on fraud, risk, or financial crime
Advanced Python and SQL
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, including 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: fintech, payments, crypto, or card fraud experience, including chargebacks and disputes
Preferred: experience with device intelligence, behavioral signals, or consortium data
Preferred: familiarity with blockchain analytics, AML, and KYC
Preferred: experience evaluating LLM or agent-based review workflows

Benefits

Comp & perks

Flexible work environment
Inclusive work environment
Equal opportunity employment
Interview accommodations or assistance for candidates with disabilities