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Toyota North America
Overview
Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world’s most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We’re looking for talented team members who want to Dream. Do. Grow. with us.
An important part of the Toyota family is Toyota Financial Services (TFS), the finance and insurance brand for Toyota and Lexus in North America. While TFS is a separate business entity, it is an essential part of this world-changing company- delivering on Toyota's vision to move people beyond what's possible. At TFS, you will help create best-in-class customer experience in an innovative, collaborative environment.
Toyota does not offer support or sponsorship of job applicants for employment-based visas or any other work authorization for this role now or in the future.
You must have the right to work in the United States and not require Toyota support or sponsorship for immigration-related employment (e.g., H-1B, O-1, E-3, H-1B1, TN, F-1 OPT, F-1 STEM OPT, F-1 CPT, TN, ‘job flexibility benefits’ (also known as I-140 or Adjustment of Status portability), etc. now or in the future.
You should not apply for this role if you will require Toyota to assist with immigration support or sponsorship now or in the future.
Who We’re Looking ForThe role reporting to the National Manager of Credit and RV Loss Forecasting will serve as a technical project lead and liaison between the Risk business unit, Data Science, Data Engineering, and Data Stewardship teams.
A core part of the role is to support the enhancement of statistical models used for Residual Value and Credit Loss forecasting by coordinating requirements, facilitating implementation, and ensuring the necessary data infrastructure is in place.
This includes working with Data Engineering to improve or build data pipelines, source inputs, output tables, and supporting data structures that feed model development and downstream risk processes.
In addition to model-support work, the role functions as the primary technical contact for Risk data inquiries and investigations. That includes responding to requests related to source data, data lineage, calculation logic, and data quality validation.
The position also helps identify opportunities to improve existing workflows, analytical processes, and model-related operations, while partnering with business stakeholders and technical teams to execute those improvements.
The ideal candidate, will require a blend of technical fluency, project management, and business acumen to ensure that risk data is accurate, traceable, and structured in a way that supports forecasting models and strategic decision-making.
What You’ll Be DoingLead enterprise and cross-functional initiatives across Risk, Data Science, Data Engineering, and Data Stewardship in support of forecasting, modeling, and risk data priorities.
Independently define, coordinate, and drive business and technical requirements through implementation, ensuring alignment to strategic objectives and operational needs.
Communicate complex technical concepts and business impacts clearly to senior stakeholders across functionsServe as a senior technical authority for risk data inquiries, investigations, enhancements, and issue resolution.
Lead complex analysis of source data, lineage, calculation logic, and data quality to ensure accuracy, traceability, and integrity of risk information.
Partner with data science teams to evaluate, prioritize, and implement enhancements to Residual Value and Credit Loss forecasting models.
Collaborate with data engineering teams to design and improve data pipelines, table structures, model inputs, and downstream data dependencies.
Work to ensure the supporting data environment is accurate, scalable, and fit for model development and operational use.
Identify, influence, and help implement process and workflow improvements that strengthen forecasting effectiveness and operational efficiency.
Drive sustainable solutions that improve model support, data management, and decision-making capabilities across the risk organization.
Work with governance and stewardship stakeholders to maintain high standards for data quality, completeness, reliability, and fit-for-purpose use.
Partner across business and technical teams to align priorities, address risks, and ensure solutions are implemented effectively and sustainably.
Utilizing advanced written and verbal communication skills.
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