Senior Data Scientist- Credit Modeling

About the position Senior Data Scientist will work in the Analytics Department of Southeast Toyota Finance (SETF), a division of JM Family Enterprises, and will be responsible for developing solutions that drive improved efficiency and quantify portfolio performance in credit risk, residual risk, collection, and recovery. This individual should comprehensively understand consumer lending and the characteristics that drive performance and profitability. They must have excellent predictive modeling skills and be able to communicate how analytical solutions can positively impact the business effectively. The individual must know advanced statistical modeling techniques and software.

Responsibilities

• Work on advanced analytics projects to produce statistically sound operational, portfolio, behavior, and recovery models that drive actionable/implementable results under aggressive deadlines.
• Quantify and communicate the credit and residual loss exposure on SETF's retail and lease portfolios incorporating different economic scenarios and seasonal trends for budgeting and reserve purposes, including CECL models and forecasts.
• Develop and implement residual value models to determine accurate residual values for leased vehicles.
• Develop operational models to help quantify and control risk while increasing efficiency/automation. This includes developing, monitoring, and deploying origination and collection scorecards and strategies.
• Develop advanced machine learning and statistical models to solve complex business challenges. Communicate model results to stakeholders. Contribute to feature engineering strategies to enhance model performance. Stay updated on the latest advancements in machine learning and data science.
• Effectively communicate complex technical concepts to stakeholders. Create visually compelling PowerBI visualizations to aid decision-making. Use advanced AI in new areas of the business.
• Manage the full modeling lifecycle of forecasting models, ensuring compliance with regulatory environments.
• 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.
• Provide comprehensive portfolio tracking, analysis, reporting, and forecasting. Provide detailed explanatory analysis and make recommendations to senior management; Proactively identifying risks and opportunities based on current trends and future outlooks.
• Present credit and residual loss trends to the executive management team.
• Develop and/or enhance advanced reporting solutions: portfolio reporting, portfolio stability reports, and model monitoring.
• Collaborate with cross-functional teams, including accounting, finance, treasury, and other company stakeholders. Mentor junior team members.

Requirements

• 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.
• Strong interpersonal and communication skills (verbal and written).
• Ability to diplomatically communicate findings across departments and to upper management.
• Ability to effectively 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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