Data Scientist - Optimization

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 Toyota North American Headquarters in Plano, TX Who we’re looking for Toyota's Digital Innovations organization is seeking a Data Scientist

• Optimization to lead the design, development, and industrialization of advanced optimization solutions supporting integrated vehicle and parts supply chain transformation. This role applies mathematical optimization, operations research, data science, and cloud-based engineering practices to help deliver the North American Vehicle Supply Chain vision of providing the right vehicle to the right place at the right time. The successful candidate will serve as a hands-on technical leader for optimization use cases across demand planning, supply allocation, production and logistics planning, ETA improvement, inventory positioning, scheduling, routing, network design, and decision automation. The role will use commercial optimization platforms such as Gurobi, along with Python-based data science ecosystems and cloud services, to translate complex business constraints into scalable decision models and production-ready products. Reporting to the General Manager of Supply Chain Transformation , this person will partner closely with business process owners, product owners, application architects, data engineers, platform teams, and executive stakeholders. The role requires strong technical depth, Toyota Way leadership, cross-functional influence, clear communication, and the ability to move advanced analytics solutions from concept to reliable operations. What you’ll be doing
• Lead the development and deployment of mathematical optimization models for integrated supply chain planning, including mixed-integer programming, linear programming, network flow, constraint programming, heuristics, simulation-informed optimization, and scenario-based decision support.
• Use optimization platforms such as Gurobi to formulate, solve, tune, and operationalize complex business problems involving capacity, allocation, sequencing, routing, inventory, production, distribution, transportation, and service-level tradeoffs.
• Translate business objectives, policies, operational constraints, and Toyota-specific process rules into data-driven optimization model structures, objective functions, constraints, decision variables, and performance measures.
• Partner with vehicle and parts business leaders to identify high-value optimization opportunities, define problem statements, quantify value, prioritize use cases, and establish measurable outcomes tied to supply chain efficiency, revenue enablement, cost reduction, service improvement, and customer/dealer experience.
• Manage and coach a team of data scientists, optimization engineers, analysts, and technical contributors; provide direction on solution design, modeling standards, code quality, experimentation discipline, and operational readiness.
• Collaborate with product owners, architects, data engineers, application developers, and cloud/platform teams to embed optimization services into digital products, APIs, workflows, and decision-support tools.
• Develop scalable data pipelines and model inputs using trusted enterprise data sources, including operational vehicle, parts, logistics, demand, production, and dealer/customer data, with appropriate focus on data quality, lineage, and traceability.
• Define model validation approaches, sensitivity analysis, back-testing methods, benchmarking, explainability, and guardrails to ensure optimization recommendations are accurate, interpretable, stable, and usable by business teams.
• Oversee the transition of optimization solutions from proof-of-concept into production, including MLOps/ModelOps practices, monitoring, retraining or re-optimization strategies, exception handling, release management, and hypercare support.
• Establish standards for scenario planning, what-if analysis, tradeoff visualization, KPI reporting, and executive storytelling to support faster and better business decisions.
• Support Agile delivery practices by defining epics, features, user stories, acceptance criteria, model requirements, test cases, and traceability from business use cases through technical implementation.
• Communicate complex optimization concepts to executive, business, and technical audiences in clear business language; influence alignment, drive buy-in, and support adoption of new decision processes.
• Continuously evaluate delivered solutions against company standards, budget expectations, operational stability, compliance requirements, model performance, and business value realization.
• Promote Toyota Way behaviors by encouraging genchi genbutsu, respect for people, continuous improvement, fact-based decision-making, and collaboration across business and technology teams.
• Practice genchi genbutsu — go to the source to learn the operation, processes, and real-world constraints firsthand, and validate problem framing with domain SMEs before formulating and committing to optimization solutions.
• Design and embed optimization within end-to-end decision workflows, partnering on workflow and process orchestration (e.g., BPMN / Camunda) so model outputs drive automated, auditable business actions. Leadership Expectations
• Serve as a technical thought leader who can set direction, and hold the team accountable for high-quality delivery.
• Operate with executive presence and communicate risks, decisions, tradeoffs, and value realization clearly to senior leadership.
• Build trust across Digital Innovations, business departments, enterprise architecture, data/platform teams, vendors, and external partners.
• Create a culture of experimentation, disciplined engineering, continuous improvement, and measurable business impact.
• Lead with curiosity and humility — prioritize deeply understanding the business operation before optimizing it, and model collaborative, question-driven behavior for the team.
• Connect the team’s optimization roadmap to enterprise direction through Hoshin and OKR planning, prioritizing and sequencing use cases against the 2–3 year supply chain transformation strategy. What you bring
• Bachelor's degree or higher in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science, Data Science, Engineering, Supply Chain Management, or a related field, or equivalent professional experience.
• Demonstrated experience building and deploying optimization models using Gurobi or comparable commercial/open-source solvers.
• Strong proficiency in Python and common data science/optimization libraries such as pandas, NumPy, SciPy, Pyomo, OR-Tools, scikit-learn, or equivalent tools.
• Experience formulating optimization problems with real-world constraints, imperfect data, competing objectives, and operational tradeoffs.
• Experience with cloud-based data and analytics platforms and with moving advanced analytics or optimization solutions into production environment