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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Engineer - Decision Scientist - **Company:** Toyota Motor Sales, U.S.A., Inc. - **Location:** Plano, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Big Data, Cloud Database, Software Quality, Code Review, Continuous Integration, Data Cleansing, Data Integration, Software Debugging, Decision Support Systems, DevOps, Python (Programming Language), Machine Learning, Natural Language Processing, Operational Databases, Software Architecture, Cloud Services, Software Engineering, SQL Databases, Systems Integration, Workflow Management Systems, Datadog, Enterprise Software Applications, Feature Engineering, GitHub Copilot, Retrieval-Augmented Generation, Large Language Models, Grafana, Prompt Engineering, Apache Spark, Model Validation, Generative AI, Agentic-AI, Git, Maintaining Code, Machine Learning Operations, Cloudwatch, Software Version Control, Amazon Redshift, Databricks - **Published:** October 26, 2026 - **Apply:** https://www.adzuna.com/details/5938053361 ## About the Role * 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 and machine learning technologies - AWS, Apache Spark, Databricks, AWS Redshift, S3 - and orchestration tools such as Apache Airflow / AWS Step Functions. * Hands-on experience with technical design, model and application development, conducting code reviews, and driving code quality. * Experience monitoring data quality, model performance, application health, and error notifications using tools such as Datadog / CloudWatch, Grafana, or comparable platforms. * Proven experience packaging and deploying analytical or machine learning capabilities through batch pipelines, APIs, dashboards, or workflow applications, with appropriate security and release practices. * Strong understanding of DevOps and MLOps practices, CI/CD pipelines, agile methodologies, and version control systems (Git). * Proven ability to work through technical challenges and complex problem-solving to deliver high-quality products, digging to root cause rather than treating symptoms and understanding the business problem before reaching for a solution. * Experience with both functional and non-functional requirements, including security, privacy, performance, scalability, explainability, and responsible AI considerations. * Excellent communication skills, with the ability to collaborate effectively across cross-functional teams. * Demonstrated use of AI tools as an assistant in your data science workflow, with the judgment to know where they help, where they do not, and how to keep quality and review standards intact. * Curiosity about emerging technology and a willingness to experiment - trying new tools and approaches, learning quickly from what does not work, and sharing what you find with the team. * Comfort working as part of a cross-functional fusion team and moving across different parts of the Supply Chain as priorities change. Added bonus if you have * Familiarity with AI concepts - machine learning, generative AI, prompt engineering, model evaluation, AI governance - and responsible-AI considerations. * Experience using GitHub Copilot within secure development workflows while maintaining code quality and review standards. * Demonstrated experience transforming large-scale applications or modernizing analytical products. * Supply Chain, manufacturing, logistics, procurement, supplier development, planning, or supplier risk experience. * Experience building with LLMs, retrieval-augmented generation, or AI agents in production data and application workflows - retrieval, tool calling, evaluation, or agentic pipelines. ## Description 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.