Quantitative Analytics Manager – Model Risk Management

OneMain is seeking a Quantitative Analytics Manager, Model Risk Management to lead and strengthen the firm’s Model Risk Management program in alignment with regulatory guidance. The role supports a diverse consumer credit portfolio and applies advanced analytics and machine learning expertise while exercising independent challenge across the full model lifecycle.

Requirements

• Master’s degree in a quantitative discipline (Statistics, Mathematics, Data Science, or related field) required; PhD preferred.
• 5+ years of experience in statistics, data science, decision science, or a related quantitative field.
• 3+ years of experience building, reviewing, or validating machine learning models within the consumer finance industry.
• Strong understanding of consumer lending products, credit risk practices, and regulatory expectations related to model risk management.
• Hands‐on experience with machine learning techniques, particularly tree‐based models such as XGBoost, and strong analytical “deep‐dive” capabilities.
• Proven ability to lead and manage complex, ambiguous projects and provide structured, defensible analytical judgment.
• Strong written and verbal communication skills, with the ability to explain complex technical concepts to non‐technical stakeholders, auditors, and regulators.
• Demonstrated intellectual curiosity, strong idea generation, and an interest in research, innovation, and continuous improvement.
• Proficiency in Python and SQL; experience with AWS and SageMaker is a strong plus.

Benefits

• Health and wellbeing options including medical, prescription, dental, vision, hearing, accident, hospital indemnity, and life insurances
• Up to 4% matching 401(k)
• Employee Stock Purchase Plan (10% share discount)
• Tuition reimbursement
• Paid time off (15 days’ vacation per year, plus 2 personal days, prorated based on start date)
• Paid sick leave as determined by state or local ordinance, prorated based on start date
• Paid holidays (11 days per year, based on start date)
• Paid volunteer time (3 days per year, prorated based on start date)