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 About the Opportunity Our client, a leader in FinTech, 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. Key Responsibilities & Deliverables 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. Required Skills & Experience 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, LightGBM, 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 FinTech 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) #J-18808-Ljbffr DeWinter Group