Data Scientist, AI Solutions
Core
Design and optimize statistical baselines and machine learning strategies for real-time fraud and AML detection across payment rails like RTP, ACH, and Wire.
Role type
hands-on IC data scientist (fraud detection)
Builds
pre-built detection models and generalized scoring logic for new clients
Domain
Fintech / Fraud Detection / AML
Deliverable
production ML models
Required skills
Python (Pandas, NumPy, Scikit-learn), SQL, statistical modeling, feature selection, performance evaluation (Precision/Recall, AUC, KS)
Preferred skills
graph theory, link analysis, unsupervised learning, anomaly detection, knowledge of payment rails (FedNow, ACH, Wire)
Technologies
Python, Pandas, NumPy, Scikit-learn, SQL
Responsibilities
Design and back-test statistical baselines and ML strategies for core solution modules; Analyze cross-industry data to identify high-risk device fingerprints and fraud patterns; Create generalized scoring models for new clients to solve the 'Cold Start' problem; Validate AI agent logic and automated fraud detection strategies; Collaborate with Product, Strategy, and Engineering teams to implement state-of-the-art ML and LLM capabilities
Seniority
Junior to Mid-level, hands-on IC
