Specialist, Yield Management - GTM AA Data Scientist

Ford Motor CompanyDearborn, MI
$85,400 - $166,600Hybrid

About The Position

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.

Requirements

  • Data expertise
  • Analytical skills
  • Data engineering skillset
  • Machine learning skillset
  • Applied AI skillset

Responsibilities

  • Own the development of core machine learning models
  • Build foundational data pipelines that feed them
  • Integrate modern AI tools (such as LLMs, Agent and APIs) into practical business applications
  • Deliver data products that directly inform business decisions
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