Data Analytics Engagement Supervisor
Summary
Lead a team of data scientists to build and deploy customer lifetime value and predictive models that personalize marketing and guide Ford’s investment decisions across North America.
Data Analytics Engagement Supervisor
Location: Dearborn, MI, United States; Hybrid
We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.
In this position...
Ford Marketing Analytics is seeking a highly capable and technically grounded Data Science Manager to lead the Customer Modeling and Lifetime Value team. This LL6 leadership role will manage a team of 4–5 data scientists responsible for developing, deploying, and continuously improving customer propensity, predictive, prescriptive, and Customer Lifetime Value (CLV) models.
This team plays a critical role in enabling more personalized, effective, and measurable marketing activity across the enterprise. The team’s work will support loyalty, retention, upsell, cross-sell, customer engagement, and marketing investment decisions, while helping Ford better understand the full value of its customer relationships.
The Data Science Manager will lead development of Ford’s enterprise CLV framework: a central model and analytical foundation that brings together customer value streams across the company. This capability will help stakeholders understand the customer base, personalize communications and treatments, prioritize investments, and improve decision-making at both customer and portfolio levels.
This individual will combine strong data science and methodological expertise with the ability to translate complex technical work into clear business value. They will partner closely with stakeholders across Marketing, FCSD, Customer Experience, Ford Credit, Integrated Services, and other functions to establish priorities, drive adoption, and integrate modeling outputs into business processes. While this role is primarily focused on North America, it may also support related customer-modeling activities in Europe and other regions.