Senior Engineer - Decision Scientist

Toyota Motor Engineering & Manufacturing North America, Inc. Company; Plano (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Toyota Motor Engineering & Manufacturing North America, Inc. in Plano, TX is seeking a Senior Engineer - Decision Scientist to join the Digital Innovations team.

You will implement and maintain high-quality data science and AI solutions that support Supply Chain transformation and deliver value to customers. You will work in fusion teams of engineers, product, and operations, moving between teams and priorities to apply modeling, analytics, and AI across the product framework, while ensuring

Qualifications

• 5+ years in data science or ML for supply chain decisions.
• Strong background in optimization or operations research.
• Proficient Python and SQL with reproducible workflows.

Responsibilities

• Develop and maintain data science and AI solutions for Supply Chain.
• Design and implement optimization and forecasting models.
• Collaborate with cross-functional teams to deploy models.
• Ensure security, privacy, and scalability of analytical services.

Skills

Optimization

Operations research

Data science

Machine learning

Python

SQL

Databricks

Cloud services

Tools

Gurobi

Job description

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.

Who we’re looking for

Toyota’s Digital Innovations group within TMNA’s Supply Chain organization is seeking a talented Senior Engineer - Decision Scientist to join our development team. This role will focus on implementing and maintaining high-quality data science and AI solutions while collaborating with senior team members to deliver value to our customers.

Reporting to the Senior Manager, Digital Innovations , the person in this role will support the Supply Chain transformation objectives and help accelerate the adoption of modern and emerging technologies and platforms.

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 you should expect to move between teams and across different parts of the Supply Chain as those priorities shift.

What you’ll be doing

• Implementing optimization, data science, and AI solutions that align with architectural decisions, responsible AI practices, and enterprise standards.
• Designing, developing, and maintaining reproducible data preparation, feature-engineering, modeling, and scoring workflows using Python, SQL, Databricks, and approved cloud services.
• Implementing and optimizing statistical, machine learning, forecasting, optimization, anomaly detection, natural language processing, and generative AI approaches that convert Supply Chain data into useful decision support.
• Working with Business Product Owners to refine requirements, analytical questions, measures of success, and acceptance criteria.
• Applying data quality, model validation, evaluation, explainability, and error-analysis techniques to ensure the accuracy, reliability, and appropriate use of delivered solutions.
• Troubleshooting and resolving data, model, and application issues to ensure smooth project execution and dependable production operation.
• Collaborating with cross-functional teams to integrate models, analytical services, dashboards, and AI capabilities into the product framework.
• Ensuring non-functional requirements - security, privacy, performance, scalability, monitoring, and system integrations - are met through effective design and development.
• Using AI as an assistant across your daily work - analysis, coding, code review, testing, debugging, and documentation - to deliver better outcomes faster, while holding quality and review standards.
• Prototyping and experimenting to answer open questions quickly: build the smallest thing that tests the idea, measure what it shows, and share what you learned - including when it does not work.
• Spending time with the planners, logistics, buyers, supplier development, and operations teams who use what you build, so solutions reflect how the work actually happens.
• Bringing new tools, techniques, and emerging technology into the team’s day-to-day practice, and helping teammates adopt what proves out.

What you bring

• Proficiency in optimization, simulation, operations research, or scenario planning for cost, sourcing, supplier, inventory, logistics, or allocation decisions and experience with solvers such as Gurobi
• Strong technical expertise in operations research, data science, machine learning, statistical analysis, and data integration, with 5+ years of hands-on experience with modern technologies.
• 5+ years of proven expertise creating end-to-end data science or machine learning solutions that handle large data volumes and support Supply Chain decisions, business analytics, or operational products.
• 3+ years of hands-on experience with Python, SQL, data preparation, model development, and reproducible analytical workflows.
• Proficient understanding and practical experience with cloud-based data a