Full-Time

Data Scientist

Optimization

Posted on 7/9/2026

Deadline 7/24/26
Toyota

Toyota

201-500 employees

Official importer, distributor, and dealer network

No salary listed

No H1B Sponsorship

Plano, TX, USA

In Person

On-site at Toyota North American Headquarters in Plano, TX.

Category
Data & Analytics (1)
Required Skills
Scikit-learn
MLOps
Python
Pandas
NumPy

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Requirements
  • 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 environments
  • Experience leading or managing multi-disciplinary teams that include data scientists, engineers, architects, product owners, application developers, and business process owners
  • Demonstrated ability to manage multiple initiatives simultaneously while balancing scope, value, risk, timeline, budget, and resource constraints
  • Excellent verbal and written communication skills, with the ability to simplify technical content for senior leaders and business stakeholders
  • Strong Agile/Scrum delivery experience, including backlog refinement, sprint planning, acceptance criteria definition, demos, and release readiness
  • Demonstrated success working in a fusion or cross-functional product team alongside product owners, domain SMEs, and engineers from diverse backgrounds
Responsibilities
  • 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
  • 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
Desired Qualifications
  • Master's degree or Ph.D. in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Data Science, or a related quantitative discipline
  • Automotive industry experience, especially in vehicle supply chain, demand and supply planning, production planning, allocation, logistics, distribution, or dealer-facing operations
  • Strong understanding of supply chain planning, logistics, manufacturing, inventory, allocation, scheduling, or transportation management processes
  • Experience with integrated business planning, sales and operations planning, network optimization, ETA improvement, vehicle ordering, production confirmation, or logistics orchestration
  • Hands-on experience with cloud services such as AWS, Azure, or GCP and with production patterns for APIs, batch optimization, event-driven optimization, and model monitoring
  • Experience designing decision-support products with user-centric workflows, scenario comparison, explainability, and adoption-focused change management
  • Experience with enterprise data governance, data quality management, and modern data platform integration
  • Supervisory or people leadership experience in a data science, analytics, optimization, or digital product organization
  • Experience with semantic data modeling or knowledge-graph engineering to represent supply chain entities, relationships, and business constraints for optimization and decision automation
  • Experience applying agentic AI and multi-agent system frameworks to decision automation (familiarity with Digital Innovations’ agentic platform, DIAL, a plus)
  • Experience deploying industrial-grade optimization or machine learning solutions that support mission-critical operational decisions
  • Experience combining optimization with machine learning, simulation, forecasting, reinforcement learning, or agentic AI to improve decision automation
  • Experience creating reusable optimization frameworks, solver tuning playbooks, model libraries, and technical standards for enterprise teams
  • A strong eye for user-centric design and storytelling that enables business users to trust, understand, and act on model recommendations

Toyota Motor LLC imports and distributes Toyota vehicles in Russia. It handles the sale of new cars through an official dealership network and supports customers with after-sales service at official service centers, along with financial products like Toyota Insurance and leasing options. The company works by acting as the exclusive importer and then using a network of authorized dealers (e.g., Major, ROLF) to retail vehicles and provide maintenance, financing, and insurance. This combination of import role, dealership-driven sales, and bundled services distinguishes it from competitors who may rely on independent distributors or lack integrated financing and insurance options. The goal is to offer the full range of Toyota vehicles in Russia with official service, financing, and insurance, ensuring a consistent customer experience across sales and after-sales activities.

Company Size

201-500

Company Stage

N/A

Total Funding

N/A

Headquarters

Russia

Founded

1997

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Simplify Jobs

Simplify's Take

What believers are saying

  • Hybrid portfolio captures accelerating EV adoption with Lada models.
  • Service network profits from used car demand amid import restrictions.
  • Telematics integration boosts retention via remote diagnostics.

What critics are saying

  • Government seizes assets like St. Petersburg plant transferred to NAMI in 2022.
  • Sanctions collapse financing; dealerships like Major exit within 12 months.
  • Parts embargo forces service centers to close in 3-9 months.

What makes Toyota unique

  • Exclusive importer of Toyota vehicles in Russia since April 2002.
  • Operates dealerships like Major and ROLF in Moscow.
  • Provides insurance and leasing alongside after-sales service.

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Benefits

Health Insurance

401(k) Company Match

401(k) Retirement Plan

Paid Holidays

Paid Vacation

Flexible Work Hours

Remote Work Options

Family Planning Benefits

Professional Development Budget

Tuition Reimbursement

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