Principal Engineer II - Data Science

Overview Who we are 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. 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, '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. This position is based out of the Toyota Motor North America Headquarters in Plano, TX. Toyota's Digital Innovations group within TMNA's Supply Chain organization is seeking a highly experienced Principal Data Scientist to lead the technical strategy and execution of Supply Chain data science and AI initiatives. This is a technical leadership role that combines deep data science expertise, architectural leadership, and accountability for delivery across complex data, analytics, and software portfolios. As a Principal Data Scientist, you will shape technical approaches, lead complex modeling and product decisions, and guide execution across development teams in alignment with business priorities. While this role is grounded in principal-level technical leadership, it also requires the ability to develop technical talent, influence delivery practices, and step into direct leadership across one or more technical teams when needed. You will partner with engineering leaders, enterprise architects, product teams, and business stakeholders to deliver reliable decision-support solutions, remove execution barriers, and drive measurable business impact, while advancing AI-enabled delivery capabilities that improve productivity, accelerate learning, and strengthen solution quality. This position reports to the Senior Manager, Digital Innovations and plays a critical role in advancing data science standards, accelerating digital transformation, and scaling delivery excellence across Supply Chain products. You will work as part of a fusion team - engineers, product, and Supply Chain operators working to a shared goal and a shared backlog, rather than a technology group taking requests from a business group. This is how Digital Innovations operates. Technical team members are assigned to fusion teams based on priority and need and move between teams and across different parts of the Supply Chain as those priorities shift; in this role you will help set teams up to succeed and keep data science practices consistent as people move. What you'll be doing Define and advance the technical approach for Supply Chain data science and AI products built on AWS, Databricks, and Azure, ensuring alignment with business priorities, enterprise architecture, data governance, and scalable delivery objectives. Lead architecture and design decisions across data science products and development teams, balancing business value, model quality, explainability, resiliency, security, maintainability, and cost optimization. Provide principal-level technical leadership across the full data science lifecycle, from discovery and problem framing through experimentation, model development, deployment, and operational support for analytics, forecasting, optimization, machine learning, and AI workloads. Mentor data scientists, machine learning engineers, technical leads, and engineering managers to elevate technical excellence and strengthen data science capability across the organization. When needed, directly lead technical work across development teams by setting priorities, coordinating execution, and establishing effective delivery rhythms across parallel workstreams. Drive disciplined execution through scaled agile delivery practices - clear user stories, defined acceptance criteria, effective dependency management, risk mitigation, and measurable outcomes across the data science product lifecycle. Work side by side with product, operations, architecture, and platform partners to turn Supply Chain priorities into actionable technical delivery plans for spend and cost analysis, supplier risk, demand forecasting, scenario planning, document intelligence, and AI-enabled decision support. Lead rigorous technical discussions and challenge model, data, and product decisions to ensure solutions meet business objectives, technical feasibility, responsible AI, data governance, and operational excellence standards. Establish and champion modern data #J-18808-Ljbffr toyota