Job DescriptionIn 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.
ResponsibilitiesWhat you'll do...- Lead and develop a team of 4-5 data scientists responsible for customer modeling, Customer Lifetime Value, and marketing decision-science capabilities.
- Establish a high-performing, collaborative team culture that emphasizes technical rigor, innovation, accountability, continuous learning, and strong business partnership.
- Coach, mentor, and support the career development and performance management of data scientists on the team.
- Lead the development and enhancement of Ford's enterprise Customer Lifetime Value modeling framework, including retail and fleet/commercial CLV capabilities.
- Define and guide a portfolio of predictive and prescriptive customer models, including propensity, retention/churn, loyalty, purchase, conquest, service, upsell, cross-sell, next-best-action, and segmentation use cases.
- Drive the use of causal inference, experimentation, marketing measurement, and uplift modeling to evaluate the incremental impact of marketing programs and customer treatments.
- Partner with business stakeholders to translate strategic objectives and ambiguous business questions into clear analytical problems, scalable data science products, and actionable recommendations.
- Help establish the customer-modeling roadmap in partnership with Marketing Analytics leadership, balancing strategic priorities, business needs, technical feasibility, and expected value.
- Ensure the team manages the full model lifecycle, including business problem definition, data sourcing, model development, validation, deployment, performance monitoring, refreshes, documentation, and adoption.
- Provide technical oversight and methodological guidance through model-design reviews, code reviews, validation processes, and data-science best practices.
- Ensure models and analytical products meet high standards for quality, reproducibility, interpretability, performance, privacy compliance, and appropriate governance.
- Partner with technical, product, data engineering, and platform teams to enable scalable deployment and access to CLV and customer-modeling outputs through tools, interfaces, and business workflows.
- Communicate complex modeling concepts, results, limitations, and recommendations clearly to technical and non-technical audiences.
- Build strong relationships with stakeholders across Marketing, FCSD, CX, Ford Credit, Integrated Services, and other enterprise partners to drive broad adoption and measurable business impact.
- Drive continuous enhancement of data science practices through emerging methods, tools, and responsible application of Generative AI capabilities.
- Provide an excellent example of and expectation for Ford+ behaviors within the Marketing Analytics team.
- Implement "Close the Loop," OKR, and Performance+ objectives and processes within Marketing Analytics.
QualificationsYou'll have....- Bachelor's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Engineering, Operations Research, Finance, Marketing Analytics, or a related quantitative field.
- 5+ years of experience in data science, advanced analytics, customer analytics, marketing analytics, decision science, or a related field.
- 2+ years of experience leading technical projects, initiatives, or teams.
- Strong experience applying predictive modeling and statistical methods to business problems.
- Strong proficiency in Python and SQL.
Even better, you may have...- Advanced degree in Data Science, Statistics, Economics, Computer Science, Engineering, Operations Research, Finance, Marketing Analytics, or a related field.
- 10+ years of relevant data science, advanced analytics, customer analytics, or marketing analytics experience.
- 5+ years of experience leading, coaching, or managing technical teams.
- Direct experience developing, operationalizing, or improving Customer Lifetime Value models.
- Experience with financial modeling, customer economics, profitability analysis, or customer value measurement.
- Deep expertise in causal inference, uplift modeling, treatment-effect estimation, experimentation, or marketing optimization.
- Experience developing customer models in support of loyalty, acquisition, retention, CRM, personalization, cross-sell, upsell, or next-best-action programs.
- Experience with cloud-based analytics and machine-learning platforms, particularly Google Cloud Platform.
- Familiarity with model deployment, MLOps, model monitoring, production analytics, and scalable data-science product development.
- Experience applying Generative AI tools and capabilities to improve data-science workflows, analytical products, or business processes.
- Experience in automotive, mobility, financial services, subscription businesses, MarTech, CRM, or marketing optimization.
- Demonstrated success driving adoption of analytical products across complex organizations and integrating model outputs into business decision processes.
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
This position is hybrid with a requirement to be onsite four or more days per week.
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