OverviewWho we're looking for To save time applying, Toyota does not offer sponsorship of job applicants for employment-based visas or any other work authorization for this position at this time. This position is based in Plano, TX.
At TFS, we're embarking on a technology transformation journey, creating next generation products and platforms. These products enable TFS to provide a best-in-class experience to our customers and partners and position us to rapidly scale to realize our vision of mobility for all by enabling freedom of movement for everyone.
At TFS, we are driving a technology transformation and developing next-generation products and platforms that deliver a best-in-class experience for our customers and partners. These capabilities enable TFS to scale efficiently and support our vision of mobility for all by expanding freedom of movement for everyone.
We are seeking a strategic and highly experienced Technical Data Science Product Owner to define the vision, roadmap, and execution of enterprise-impacting data science products and capabilities. This role operates at the Senior Product Manager level within the product job family and is accountable for setting product direction, aligning cross-functional stakeholders, and delivering measurable business outcomes through data science, machine learning, and analytics solutions.
This position functions as a senior product leader across business, technology, data science, engineering, and analytics organizations. The ideal candidate will demonstrate strong product leadership, deep expertise in the data science lifecycle, and the ability to translate business strategy into prioritized product outcomes. This individual will influence roadmap decisions, guide product direction, and ensure data science investments are delivered with quality, scalability, and business value.
What you'll be doing - Define and refine requirements for machine learning models, decisioning tools, analytical products, and automated capabilities. Ensure requirements address data inputs, expected outputs, edge cases, business rules, performance thresholds, monitoring needs, and success measures.
- Partner with data science, QA, and business stakeholders to define model validation criteria, business acceptance standards, and release readiness expectations. Confirm solutions are technically sound, operationally ready, and aligned to the intended use case.
- Own the strategy, vision, and prioritized roadmap for one or more strategic data science products, platforms, or capabilities. Translate enterprise and business objectives into product direction, delivery themes, and measurable outcomes that support customer, operational, and financial goals.
- Partner with senior business leaders, product managers, data scientists, engineers, risk partners, and operational teams to define priorities, clarify tradeoffs, and drive alignment across competing needs. Influence senior stakeholders on scope, sequencing, and investment decisions based on business value, feasibility, risk, and strategic fit.
- Contribute to product operating model maturity, strengthen prioritization and delivery practices, and help coach junior product team members as needed. Bring a product leadership mindset that balances customer needs, business outcomes, and technical execution.
- Lead complex cross-functional delivery efforts from discovery through release and adoption. Ensure product requirements, user stories, acceptance criteria, and implementation plans are clearly defined and aligned to roadmap priorities.
- Coordinate dependencies across business, technology, data, and governance teams to enable timely and high-quality delivery. Identify and escalate risks, remove blockers, and maintain clear communication throughout the product lifecycle.
- Define and refine requirements for machine learning models, decisioning tools, analytical products, and automated capabilities. Ensure requirements address data inputs, expected outputs, edge cases, business rules, performance thresholds, monitoring needs, and success measures.
- Partner with data science, QA, and business stakeholders to define model validation criteria, business acceptance standards, and release readiness expectations. Confirm solutions are technically sound, operationally ready, and aligned to the intended use case.
- Define and track KPIs, model performance measures, experiment results, adoption metrics, and business impact indicators. Use data and insights to inform roadmap adjustments, optimize product performance, and communicate value to leadership.
- Maintain strong documentation for product requirements, assumptions, decisions, release notes, and change impacts. Support governance, traceability, and controls for data science and analytic solutions in accordance with internal standards and applicable regulatory expectations.
- Contribute to product operating model maturity, strengthen prioritization and delivery practices, and help coach junior product team members as needed. Bring a product leadership mindset that balances customer needs, business outcomes, and technical execution.
What you bring- Bachelor's degree in Business, Computer Science, Information Systems, Engineering, Data Science, Statistics, Mathematics, Economics, or a related field, or relevant experience
- 7+ years of relevant experience in product ownership, business analysis, analytics, or delivery coordination in a technical or data-driven environment
- Experience and understanding of Agile frameworks and product backlog management
- Practical understanding of how data science products are built and operated - enough to write credible requirements, evaluate trade offs and be substantive counter part to data scientists and ML engineers without building models directly
- Experience using Jira, GitHub, Confluence, and similar collaboration tools
- Experience with data science concepts such as model development, experimentation, deployment, and monitoring
- Experience with SQL, Python, reporting, dashboards, or analytics tools
Added bonus if you have- Experience with A/B testing or experimental design
- Familiarity with machine learning lifecycle or MLE/ practices
- Experience working with data pipelines, feature engineering, dashboards, or data quality frameworks
- Experience in financial services or banking
- Experience with cloud environments such as AWS
- Experience mentoring product owners, analysts, or delivery leads
- Experience influencing roadmap or investment decisions at an enterprise level
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 advance your 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 as an annual retirement contribution from Toyota regardless of whether you 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 Care FSA, Dependent Care FSA) Relocation assistance (if applicable)
