We are hiring a Data Scientist to join the Quality Analytics team within Global Data Insight and Analytics (GDI&A). This role focuses on delivering end‑to‑end machine learning and AI solutions that improve product quality, reliability, and customer outcomes. The ideal candidate has hands‑on experience applying machine learning, LLMs, and graph‑based approaches in production‑oriented environments.

Required Qualifications

• Master’s degree (required) in Data Science, Machine Learning, Statistics, Computer Science, Industrial Engineering, or related field.
• 2+ years of experience delivering production‑relevant ML or advanced analytics projects.
• 2+ years of experience using Python and common ML/DS libraries (e.g., scikit‑learn, Py Torch/Tensor Flow, SQL).
• 2+ years of hands‑on experience in machine learning model development, experimentation, and evaluation.
• 2+ years of experience applying or integrating Large Language Models (LLMs) into real analytics workflows.
• 2+ years of experience working with cloud‑based data and ML platforms, preferably GCP.

Preferred Qualifications

• PhD in Data Science, Machine Learning, Statistics, Computer Science, Industrial Engineering, or related field.
• Experience with Knowledge Graphs, graph databases, or graph‑augmented ML/LLM systems.
• Familiarity with RAG architectures, vector search, or hybrid retrieval systems.
• Experience in quality, warranty, manufacturing, or industrial analytics.
• Exposure to MLOps practices (CI/CD, model monitoring, retraining).

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!As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:

• Immediate medical, dental, and prescription drug coverage• Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care 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.

For a detailed look at our benefits, click here: Benefit Summary This role is remote but if you live within 50 miles of a Ford Hub (Dearborn, MI or Palo Alto), you will be required on-site 4x a week.Visa Sponsorship IS provided for this specific role Relocation assistance IS provided for this specific role 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 committed to a culturally diverse workforce. 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 1-888-336-0660.

GSR7

• Design and deliver end‑to‑end data science solutions, from problem formulation through modeling, evaluation, and deployment support.
• Develop and evaluate machine learning models (e.g., classification, anomaly detection, forecasting, NLP) for quality and reliability use cases.
• Build LLM‑enabled applications, including prompt‑based systems, RAG pipelines, and hybrid ML + LLM solutions.
• Leverage Knowledge Graphs and graph‑based techniques to integrate structured and unstructured data.
• Implement data and ML workflows on cloud platforms, preferably Google Cloud Platform (GCP).
• Write high‑quality, reproducible, and maintainable code and collaborate with cross‑functional stakeholders.