Senior Data Scientist – Go-to-Market Advanced Analytics (Yield Management)

Ford • Dearborn, MI

1d • $68,300 - $192,900 • Hybrid

About The Position

The Senior Data Scientist will join Ford’s Yield Management Advanced Analytics team, which develops and maintains modeling and optimization capabilities used to guide pricing and incentive strategy. The role collaborates with analytics product teams, data engineering, AI/ML engineering, and business stakeholders to create quantitative solutions that inform vehicle pricing, incentive structure, and portfolio risk management.

The successful candidate serves as a subject matter expert for analytical products and owns solutions throughout their lifecycle, from framework design through production deployment and ongoing maintenance. Deliverables may include always-on web applications such as Python Dash apps, ad-hoc analyses, or dashboards. The position applies statistical modeling, machine learning, and optimization to business constraints, and may explore agentic AI and LLM-based workflows to improve analytical delivery.

The position is hybrid and requires being onsite four or more days per week. Ford offers medical, dental, vision, and prescription coverage; family-care and parental supports; family-building benefits; employee and family vehicle discounts and management leases; tuition assistance; employee resource groups; paid community-service time; paid holidays; paid time off; and the option to purchase additional vacation time. Salary grade is 5–8, with a stated range of $68,300–$192,900. Visa sponsorship is available.

Requirements

• Master’s degree in Data Science, Statistics, Economics/Econometrics, Mathematics, Operations Research, Artificial Intelligence, Machine Learning, or a related quantitative field.
• At least 3 years of experience in data analytics, AI/ML modeling, or related quantitative analysis.
• Proficiency in one or more programming languages: Python, R, MATLAB, C/C++/C#, or SAS.
• Familiarity with machine learning/deep learning libraries and SQL.

Nice To Haves

• Ph.D. in Data Science, Statistics, Economics/Econometrics, Mathematics, Operations Research, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Demonstrated experience applying econometrics, statistics, and/or machine learning or deep learning to large structured and unstructured datasets.
• Strong problem formulation and analytical rigor, with the ability to interpret and communicate model results.
• Experience with web application frameworks such as Dash, Flask, or Streamlit; version control such as Git; and cloud platforms such as Azure or GCP.
• Curiosity or experience exploring agentic AI and LLM-based tools, with interest in applying them to analytical workflows.

Responsibilities

• Own the end-to-end lifecycle of complex predictive models and optimization frameworks, including scheduled updates, continuous improvement, and maintenance.
• Serve as a subject matter expert for analytical products and ensure the accuracy of their data, calculation logic, and business assumptions.
• Transition analytical frameworks into production-ready assets, with an emphasis on deployment automation, operational stability, and clean, modular, well-documented code.
• Explore emerging techniques, including agentic AI and LLM-based tools, to improve modeling workflows or analytical delivery.
• Partner with business stakeholders to understand evolving needs and translate ambiguous business problems into well-defined analytical problems.
• Communicate quantitative concepts and results clearly to technical peers and business partners so the work supports actionable decisions.
• Execute rapid-response, ad-hoc analyses for time-sensitive strategic decision-making.
• Collaborate with data engineering, AI/ML engineering, and other Yield Management analytics product teams to align data science capabilities with business needs.
• Assess portfolio risk and opportunity at portfolio or nameplate level.
• Assess business impacts of incentive tactics to support incentive planning.
• Optimize nameplate profitability or minimize risk by adjusting entity-level pricing in light of production, market demand, and operational constraints.
• Support new model-year launches, mid-year repricing, and short-term variable marketing adjustments.

Benefits

• Immediate medical, dental, vision, and prescription drug coverage.
• Flexible family care days, paid parental leave, new parent ramp-up programs, and subsidized backup childcare.
• Family-building benefits, including adoption and surrogacy expense reimbursement and fertility treatments.
• Vehicle discount program for employees and family members and management leases.
• Tuition assistance.
• Established and active employee resource groups.
• Paid time off for individual and team community service.
• Paid holidays, including the week between Christmas and New Year’s Day.
• Paid time off and the option to purchase additional vacation time.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior