Senior 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 Global Data Insight & Analytics 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 Global Data Insight & Analytics (GDIA), 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 GDIA Cost Efficiency Analytics team develops data products, analytic software and provides insights to a broad range of skill teams and delivers value to Ford using critical thinking, artificial intelligence (AI), machine learning (ML), and optimization techniques.

As a Senior Data Scientist, DCC, you will use your knowledge of data and advanced analytics to identify and articulate the role data and analytics products play in helping the business achieve its goals. You will develop analytics products using your expertise in visualization, AI/ML, statistics and optimization using GDI&A approved packages and architectures. You will collaborate with Data Engineers and Software Engineers to develop robust analytics products.

You will use your knowledge of the product‑driven operating model, analytic and software delivery via Google Cloud Platform to optimize the delivery of value. You will interact with business partners in Cost efficiency analytics to align with their needs and processes to ensure relevance of products.

Based in Dearborn, MI, this is a hybrid position with a required four‑day onsite presence each week.

• Model Development and Optimization:
  Design, train, and fine‑tune AI models (including deep learning and LLMs) to solve specific business problems.
• Familiar with LLM orchestration workflows like Crew.ai, Langraph, Google ADK for quick development and scaling strategies to build robust pipelines.
• Deployment and Integration:
  Transition models from research environments to production, often by converting them into APIs or integrating them into existing software applications.
• Infrastructure Management:
  Build and maintain the infrastructure for AI development, data pipelines, and automated workflows.
• Collaboration:
  
  Work with data scientists to define AI strategies, understand requirements, and implement solutions.
• Performance Evaluation:
  Test, validate and monitor AI models at production scale to ensure reliability.
• Research and Innovation:
  Stay current with AI advancements (generative AI, LLMs) and apply them to improve existing products.

• Accelerate the application of value‑added analytics and machine learning into the portfolio of products for CEA.
• Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
• Work closely with the Product Manager and Product Owner to translate business value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
• Work hands‑on with the team and other partners to deliver solutions that meet our customers’ requirements and needs.
• Act as a consultant to the business vs. an order taker.
• Balance “doing it right” with “speed to delivery” by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.

• Master’s degree in a quantitative field such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics,…