Senior Data Scientist

Ford is undergoing its most significant transformation in over a century, and our manufacturing plants are at the heart of this evolution. In this role, you will sit within the ATP organization, focusing specifically on the "smart factory" initiative. You will be responsible for developing, deploying, and scaling machine learning models that address critical manufacturing challenges: predictive maintenance for robotics, real‑time anomaly detection on the assembly line, and automated quality control.

This is a technical Individual Contributor (IC) role that requires a deep understanding of the full data science lifecycle. You won’t just be building models in a vacuum; you will work cross‑functionally with Product Managers, Industrial Designers, and Plant Engineers to ensure your solutions are robust, scalable, and integrated into the physical workflow of our factories. You will be a key player in Ford’s transition to a software‑defined manufacturing powerhouse.

Minimum Requirements:

• Education: Requires a bachelor’s or foreign equivalent degree in computer science, information technology or a technology related field
• Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related quantitative field.
• Experience: 5+ years of professional experience in a Data Science role, with a proven track record of deploying models into production environments.
• Technical Stack:
  • Proficiency in Python (R and SQL are also highly valued).
  • Expertise in machine learning frameworks:
    Py Torch ,
    Tensor Flow
    , Scikit‑learn
    , XGBoost
    , and LightGBM
    .
  • Experience working within Google Cloud Platform (GCP) (Vertex AI, Big Query, Dataflow).
• Domain Knowledge: Previous experience with time‑series analysis, industrial IoT data, or manufacturing quality systems.

Preferred Requirements:

• Advanced Degree: PhD in a relevant field.
• Deep Learning: Experience with Computer Vision (CNNs) for automated inspection or Transformers for complex sequence modeling in sensor data.
• MLOps: Familiarity with CI/CD for machine learning, containerization (Docker/Kubernetes), and model monitoring tools.
• Communication: Ability to explain complex mathematical concepts to non‑technical stakeholders (e.g., plant managers and design leads).
• Problem‑Solving: A "product‑first" mindset—focusing on the business impact of the model rather than just its accuracy metrics.

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 change maker, 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, :
Benefit Summary

This position is a salary grade 8.

This position is a salary grade 8 and ranges from $,980
.

* Visa Sponsorship is provided for this 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…