The Senior Data Scientist - Credit Risk Modeler will work in the Analytics Department of Southeast Toyota Finance (SETF), which is part of JM Family Enterprises. They will lead the development, validation, and implementation of CECL models and frameworks at the account level., * Lead the development and implementation of account-level loss forecasting models- Probability of Default, Exposure at Default, Loss Given Default, Prepay curves or models, and other forward-looking credit risk models.

• Develop and maintain documentation, code, and implementation documents in compliance with best practices and standards.
• Perform back testing and benchmarking exercises to ensure model accuracy and robustness.
• Conduct assessments for overlays/adjustments and maintain accurate documentation in accordance with best practices and standards.
• Analyze large datasets in a panel framework with the ability to perform sampling, exploratory analysis, outlier analysis, standardization, data transformation, and segmentation analysis.
• Conduct stress testing, scenario analysis and sensitivity testing.
• Proficiently communicate complex technical concepts to stakeholders.
• Work on end-to-end modeling processes, including data procurement, model estimation, implementation and deployment, and monitoring and testing.
• Provide insights from the models and modeling exercises to support business risk management and strategies.
• Track the portfolio in detail. Analyze and report on the findings. Provide forecasts. Provide detailed explanatory analysis and make recommendations to senior management; Proactively identifying risks and opportunities based on current trends and future outlooks.
• Collaborate with cross-functional teams, including accounting, finance, risk, and other company stakeholders.

This individual will need to have a solid statistical, mathematical and programming skills with experience in credit risk modeling. This role requires cross-functional collaboration with partner teams such as Finance and Accounting to ensure accurate estimation of credit losses., * A master’s or Ph.D. degree in statistics, data science, operations research, mathematics, and/or other quantitative analysis is required

• 5+ years of financial, credit risk, and analytics resource management; indirect automotive lending experience and/or consumer lending preferred.
• Minimum of 5 years of statistical modeling and/or quantitative analysis experience
• Experience in using Python, SAS, R, or any comparable statistical or data extraction software is preferred.
• Experience managing advanced modeling projects and collaborating well with other team members.
• Well-developed interpersonal and communication skills (verbal and written)
• Ability to diplomatically communicate findings across departments and to upper management.
• Ability to successfully operate with multiple priorities and changing directives. Self-motivated with the ability to anticipate department needs, discern work priorities, and meet deadlines.
• Forward thinker who actively seeks opportunities and proposes solutions.
• Must be a highly detailed process-driven individual who demonstrates success at building trust and influence while driving for results with and through people.

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