ML Engineer - Fraud Risk​/AI Data Science

Job Details

Title: ML Engineer - Fraud Risk/AI Data Science

Job Type: Contract

Contract Length: 4-5 months

Pay Range: 80-85/hr

Target

Start Date:

3/11

Location: Remote

Our client, a leader in Fin Tech, is looking for a skilled ML Engineer - Fraud Risk/AI Data Science to join their team for a 4-5 month engagement. This project involves designing, building, and deploying machine learning models to predict fraud risk in a real‑time environment, and building efficient, reusable data pipelines. This is a high‑impact role that requires a self‑motivated professional who can hit the ground running and deliver results quickly.

• Assist in development, validation, and maintenance of real‑time features.
• Design, build, evaluate, and defend machine learning models to predict fraud risk.
• Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python and SQL.
• Deploy models in a production environment in collaboration with other data scientists and engineering teams.
• Collaborate with business partners to create policies utilizing model results.
• Implement metrics like AUC, KS, and Gini to monitor/measure model performance, and PSI/CSI to measure stability indices.
• Ensure model fairness, interpretability, and compliance with FCRA, ECOA, and other relevant regulatory frameworks.

• 2+ years of industrial experience in Data Science, Machine Learning, and related areas.
• A Degree in Mathematics, Statistics, Computer Science, or a related field.
• Deep expertise in:
  • Python and SQL;
    Strong proficiency in Python with libraries such as scikit-learn, XGBoost, Light
    
    GBM, pandas, and numpy.
  • A variety of machine learning techniques, including tree‑based models, regression models, time‑series, causal analysis, and clustering.
  • Credit risk modeling concepts, including PD calibration, reject inference, adverse action logic, and risk segmentation, preferably in a credit risk/lending or Fin Tech domain.
• Demonstrated ability to work autonomously and manage your own time effectively to meet project goals.
• Experience with tax and/or credit bureau data in credit model development.
• Familiarity with cash flow data as alternative or complementary data sources.
• Strong business problem solving, communication, and collaboration skills.

W2 only (No C2C or 1099 contractors)