Risk Analyst II - Portfolio Forecasting
GM Financial
Why GM Financial? GM Financial is the wholly owned captive finance subsidiary of General Motors, headquartered in Fort Worth, U.S. We are a global provider of auto finance solutions, operating in North America, South America, and the Asia Pacific region. Through long‑standing relationships with auto dealers, we offer attractive retail financing and lease programs to meet the needs of each customer. We also offer commercial lending products to help dealers finance and grow their businesses. Job Description The Risk Analyst II – Portfolio Forecasting is responsible for assisting in the design, development, and maintenance of complex portfolio forecasting models. These models support corporate planning, financing, and account servicing operations. The role also analyzes and reports on factors that affect portfolio performance, such as delinquency, loss frequency, loss severity, bankruptcies, and payoffs. This position will remain open until filled. Responsibilities Assist in the design, development, and maintenance of sophisticated portfolio forecasting models. Utilize data mining and advanced spreadsheet/technical skills to participate in complex forecasting, modeling, analysis, and reporting related to portfolio performance factors. Employ best practices of data analysis and validation to ensure data results are accurate. Promote innovative ways to visualize and digest complex data. Proactively monitor and report relevant changes in portfolio performance to management. Effectively summarize and communicate portfolio performance trends, expectations, forecast methodology, and results to management. Provide direction, training, and guidance to less experienced analysts and lead projects or assignments as required. Qualifications Demonstrated understanding of data mining, data analysis and visualization, quantitative and analytical methods, and sophisticated forecasting techniques. Advanced proficiency with Microsoft Excel, PowerPoint, and Word. Experience with data analysis and spreadsheet modeling and/or reporting. Experience with coding (SAS or SQL preferred) for data mining and transformation in a data warehouse environment. Demonstrated quantitative skills. Acute attention to detail. Effective written and verbal presentation skills. Capable of managing multiple projects, balancing numerous tasks in a time‑sensitive environment, under pressure, and meeting deadlines. Ability to identify and understand business issues and map them into quantitative questions. Understanding of the metrics used in monitoring the performance of a consumer lending portfolio is a plus. Experience & Education Normal office environment. Limited travel may be required to support business needs. 2–4 years experience working with complex Excel workbooks, querying large multi‑table datasets, data analysis, and data presentation; proficiency with SAS and/or SQL, Microsoft Excel, PowerPoint, and Word. 2–4 years experience in consumer loan or lease portfolio analysis, reporting, and/or forecasting preferred. Bachelor’s degree in Finance, Economics, Mathematics, Business, Business Analytics, MIS, or another quantitative field; degrees in non‑quantitative fields considered with adequate work experience. Benefits Generous benefits package available on day one, including 401(k) matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay, and nine company holidays. Competitive pay and bonus eligibility. Flexible hybrid work environment (2 days a week in the office). NOTE: We are unable to consider candidates who require visa sponsorship for this position. #J-18808-Ljbffr
- ...Risk Analyst II – Portfolio Forecasting GM Financial is the wholly owned captive finance subsidiary of General Motors and is headquartered in Fort Worth, U.S. We are a global provider of auto finance solutions, with operations in North America, South America, and the...SuggestedWork experience placementWork at officeVisa sponsorshipFlexible hours2 days per week
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