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

Ford Motor • Dearborn, MI

2d • Hybrid

About The Position

The Senior Data Scientist is part of Ford’s Yield Management Advanced Analytics team, which develops and maintains modeling and optimization capabilities for pricing and incentive strategy. The role partners with analytics product teams, data engineering, AI/ML engineering, and business stakeholders to create quantitative solutions that inform vehicle pricing, incentive structures, and portfolio risk management.

The successful candidate serves as a subject matter expert on analytical products and translates complex business problems into rigorous quantitative solutions. They own solutions through their full lifecycle, from framework design to production deployment and ongoing maintenance. Deliverables may include always-on web applications, such as Python Dash apps, as well as ad-hoc analyses and dashboards. The role applies statistical modeling, machine learning, and optimization to real business constraints, and may explore agentic AI and LLM-based workflows to improve analytical processes and delivery.

Key business questions include assessing portfolio or nameplate-level risk and opportunity; evaluating the effects of incentive tactics; optimizing nameplate profitability or reducing risk through entity-level pricing adjustments; and supporting new model year launches, mid-year repricing, and short-term variable marketing adjustments. The position is hybrid and requires onsite work four or more days per week.

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.
• Legally authorized to work in the United States; employment eligibility will be verified at hire.

Nice To Haves

• Ph.D. in Data Science, Statistics, Economics/Econometrics, Mathematics, Operations Research, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Demonstrated ability to apply econometrics, statistics, and/or machine learning or deep learning techniques 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, and interest in applying them to analytical workflows.

Responsibilities

• Own the lifecycle of complex predictive models and optimization frameworks, including scheduled updates, continuous improvement, and maintenance.
• Serve as a subject matter expert for analytical products, ensuring the accuracy of data, calculation logic, and business assumptions.
• Transition analytical frameworks into production-ready assets, with attention to 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 actionable insights to technical peers and business partners.
• 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 or nameplate-level risk and opportunity.
• Evaluate the business impact of incentive tactics to support incentive planning.
• Optimize nameplate profitability or minimize risk by adjusting entity-level pricing based on 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.
• 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