Specialist, Yield Management - GTM AA Data Scientist

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. Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics and analytics, as well as insightful interpreters and analysts. That's where Yield Management makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making. In Yield Management , we aspire to navigate Ford Motor Company through the disruptiveness of the information age, harnessing the power of data and artificial intelligence to realize the enterprise’s known goals, reveal hidden opportunities, and achieve data superiority. The Go-To-Market (GTM) team develops data products and provides insights to a broad range of skill teams across Ford. As a Data Scientist , you will play a critical, hybrid role on our team. You will own the development of core machine learning models while also building the foundational data pipelines that feed them and integrating modern AI tools (such as LLMs, Agent and APIs) into practical business applications. This is a unique opportunity to apply a highly versatile, end-to-end technical skillset—spanning data engineering, machine learning, and applied AI—to deliver data products that directly inform business decisions. Based in Dearborn, MI , this is a hybrid position with a required 4‑day onsite presence each week. What You’ll Do Model Development & Analytics: Design, train, and evaluate machine learning models, including predictive, classification, and ensemble methods, and conduct exploratory data analysis to surface trends, anomalies, and decision-support signals AI Application & LLM Integration: Build and integrate LLM powered workflows for insight generation and decision support, blending structured business metrics with external signals through effective prompt engineering and harness in the agent Data Pipeline & Engineering: Design, build, and maintain scalable ETL and data pipelines across multi‑source datasets to power analytics, reporting, and downstream applications Data Products & Visualization: Develop interactive analytics applications and dashboards (such as Dash/PowerBI) that deliver real‑time analytics, KPI monitoring, and actionable business insights Model Evaluation & Data Quality: Establish model evaluation frameworks grounded in statistical metrics and business KPIs, and safeguard data reliability through validation of completeness, consistency, and ongoing pipeline monitoring Collaboration & Delivery: Partner with data engineers, software engineers, and product owners to translate business needs into robust analytic deliverables, balancing technical rigor with speed to delivery You'll Have Bachelor’s degree in a quantitative field, such as Data Science, Statistics, Computer Science, Mathematics, or an equivalent combination of relevant education and experience 3+ years of hands‑on experience applying Python and SQL to data analysis and machine learning Solid understanding of core machine learning algorithms, statistical methods, and model evaluation techniques Demonstrated experience working with both structured and unstructured data Even Better, You May Have Master’s degree in a quantitative field, such as Data Science, Computer Science, Statistics, or Mathematics Experience with cloud platforms (such as Google Cloud Platform, AWS, or Azure) for analytics and model deployment Exposure to Generative AI, Large Language Models (LLMs), prompt engineering, or AI agent frameworks Familiarity with data pipeline and engineering tools (such as PySpark, Airflow, or BigQuery) Experience with data visualization tools (such as PowerBI, Tableau, or Dash) Strong communication skills, with the ability to translate complex technical concepts into clear, actionable insights An inquisitive, proactive mindset with a genuine desire to learn new tools and techniques 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! Benefits Immediate medical, dental, vision and prescription drug coverage Flexible family care days, paid parental leave, new parent ramp‑up programs, subsidized back‑up child care and more Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more 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 A generous schedule of paid holidays, including the week between Christmas and New Year’s Day Paid time off and the option to purchase additional vacation time This position is a salary grade 6‑7 and ranges from $85,400-$166,600. Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value. Visa sponsorship is available for this position. Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call View phone number on click.appcast.io. This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week. #J-18808-Ljbffr Ford Motor Company