Credit Risk Modeler

MUST BE ON W2 - NO THIRD PARTY RECRUITERS?SUBVENDING PERMITTED Job Title: Credit Risk Modeler - Predictive/Credit/Stress Testing Start Date: September 15, 2025 End Date: October 30, 2026 (end of fiscal year; 13-month contract) Location: Charlotte, NC – Hybrid (2 days onsite, moving to 4 days onsite as of Nov 3, 2025) Schedule: 40 hours/week (core business hours) Overview We are seeking an experienced Data Modeler to join a Risk Model Development team, supporting the MST2.0 framework for stress testing credit loss models. This role involves extensive data mining, predictive modeling, and dashboard development to deliver insights on credit risk drivers and expected credit losses. The successful candidate will collaborate with risk management, finance, and product teams to ensure compliance with model risk policies and provide actionable analysis to support portfolio management and profitability. Responsibilities • Validate, compile, and analyze datasets for retail credit products. • Develop dashboards to highlight trends in expected credit losses and credit risk drivers. • Apply predictive modeling techniques, including scorecards and machine learning algorithms, to support stress testing and portfolio analysis. • Support model validation, review, and compliance with internal model risk policies. • Partner with retail risk management and finance teams to present data-driven insights and recommendations. • Conduct data mining on large credit risk databases using advanced statistical techniques. • Contribute to methodology development, documentation, and continuous process improvements. Must-Have Qualifications • 5+ years of experience in data modeling, predictive analytics, or risk modeling. • Strong knowledge of predictive modeling techniques, including machine learning. • Bachelor’s degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Econometrics, Operations Research). Advanced degree is an asset. • Proficiency in statistical programming tools (SAS, Python, R, Scala, Spark). • Strong problem-solving skills and ability to work independently in a fast-paced environment. Nice-to-Have • Experience with dashboarding tools such as Tableau. • Familiarity with retail credit risk, credit scoring, and portfolio management.