What you'll be doing:
Implementing 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 Strong technical expertise in 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. Proficiency in supervised and unsupervised learning, time-series forecasting, anomaly detection, feature engineering, model evaluation, and data science libraries such as pandas, NumPy, scikit-learn, PySpark, PyTorch, TensorFlow, or equivalent tools. 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 Experience with optimization, simulation, operations research, or scenario planning for cost, sourcing, supplier, inventory, logistics, or capacity decisions. Experience building AI/ML data pipelines, feature-engineering workflows, and scalable data products for model development. Experience preparing structured and unstructured data for model training, inference, document intelligence, and automation use cases. 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. AWS Certified Machine Learning Engineer (Associate), AWS Certified Data Engineer (Associate), Databricks, or equivalent cloud certifications. 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. What we'll bring During your interview process, our team can fill you in on all the details of our industry-leading benefits and career development opportunities. A few highlights include:
- A work environment built on teamwork, flexibility, and respect
- Professional growth and development programs to help advanceyour career, as well as tuition reimbursement
- Team Member Vehicle Purchase Discount
- Toyota Team Member Lease Vehicle Program (if applicable)
- Comprehensive health care and wellness plans for your entire family
- Toyota 401(k) Savings Plan featuring a company match, as well asan annual retirement contribution from Toyota regardless of whetheryou contribute (if applicable)
- Paid holidays and paid time off
- Referral services related to prenatal services, adoption, childcare, schools and more
- Tax Advantaged Accounts (Health Savings Account, Health CareFSA, Dependent Care FSA)
- Relocation assistance (if applicable) Belonging at ToyotaOur success begins and ends with our people. We embrace all perspectives and value unique human experiences. Respect for all is our North Star.
Applicants for our positions are considered without regard to race, ethnicity, national origin, sex, sexual orientation, gender identity or expression, age, disability, religion, military or veteran status, or any other characteristics protected by law.
Have a question, need assistance with your application or do you require any special accommodations? Please send an email to talent.acquisition@toyota.com.
