Senior Data Scientist Risk Management

Overview

Provide independent effective challenge to the models developed by the organization's business units. This includes conducting model validation, statistical analyses, building benchmark/challenger models, assessing model risk, assessing model performance, ensuring documentation completeness, and identifying and presenting findings to various stakeholders within the business units. Conduct work assignments of increasing complexity, under moderate supervision with some latitude for independent judgment. Intermediate professional within field; requires moderate skill set and proficiency in discipline.

Responsibilities

• Conduct model validations by evaluating conceptual soundness, assessing data suitability, reviewing statistical and analytical tests, performing outcome evaluation, and monitoring performance
• Provide subject matter expertise to identify key model assumptions, limitations, and weaknesses, and suggest solutions to address model risk
• Develop benchmark or challenger models to evaluate the robustness of the model under review
• Prepare and present comprehensive reports to model developers and owners, outlining the analyses conducted, results obtained, and recommendations for improvement
• Perform additional assigned duties as required

Qualifications

• Excellent technical writing
• Proficient in R, Python, and SAS for analyzing large datasets and building/validating predictive models
• Strong knowledge of analytical models, including generalized linear models, competing risk hazard, time series, and machine learning (e.g., XGBoost, Random Forest)
• Preferably 2+ years in model development or validation in the areas of Underwriting, Credit Risk Strategy, CECL, Stress Testing/Capital Planning, Collections, or Fair Lending.
• Preferably thorough understanding of model governance across the model life cycle
• Preferably familiarity with Navy Federal Credit Union's instructions, standards, and procedures

Desired Qualifications

• Master or PhD in Statistics, Mathematics, Economics, Computer Science, Engineering, or a related quantitative field, or equivalent experience

Hours: Monday - Friday, 8:00AM - 4:30PM

Location: 820 Follin Lane, Vienna, VA 22180

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