Quantitative Analytics Tech Lead

About the Role

Key Responsibilities

• Developing analytical methods and models that assess the credit risk of new and existing financial and mortgage products.
• Providing innovative, detailed, and practical solutions to a range of fast-paced and complex problems.
• Developing and validating loss forecasting models, researching improvements to existing models, and applying industry-standard methodologies to meet business needs.
• Coordinating testing through model implementation, conducting back tests to monitor performance, and performing economic and stress tests to validate forecast results.
• Providing modeling and analytical support to a line of business or product area as a day-to-day technical specialist.
• Preparing documentation for technical analytics and rationale during model development to ensure compliance and support model review for approval.
• Working independently to determine and develop approaches to solutions with limited direction.

Requirements

• PhD in Statistics, Math, Economics, Computer Science, or a related quantitative field with at least 3 years of post-graduate work experience, or a Master's degree with at least 5 years of related experience.
• At least three years of experience in model development including logistic regression.
• Strong programming skills in SAS, SQL, and Unix.
• Experience with programming languages such as Python, R, VBA, Java, or C++.
• Experience working with large data sets and relational databases.
• Experience working with mortgage or consumer credit risk models, prepayment models, and severity models.
• Experience with competing-risk hazard models, transition models, loss forecasting, and stress testing.
• Experience in data science, machine learning, and related technologies.
• Outstanding quantitative, empirical analysis, and research skills.
• Solid understanding of econometric models, tools, and techniques.

Nice to Have

• Experience working with industry-standard methodologies for credit risk modeling.
• Familiarity with regulatory mandates and best practices for model validation and oversight.

Qualifications

• Educational background as specified in the requirements (PhD or Master’s degree in relevant fields).

Benefits & Perks

• Competitive compensation and market-leading benefit programs.
• Participation in an annual incentive program.
• Total rewards package including comprehensive benefits.