Senior Data Scientist

Ford MotorRedford, MI
Hybrid

About The Position

We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we’re all a part of something bigger than ourselves. Are you ready to change the way the world moves? As the Senior Data Scientist for Manufacturing AI & OT Data Strategy, you will play a multifaceted role combining strategic leadership and hands-on technical expertise. You will be responsible for overseeing the end-to-end lifecycle of data science projects, from initial problem definition and data acquisition to the deployment and continuous monitoring of models. You will serve as a key liaison between Manufacturing Operations, Engineering, and IT teams to translate complex industrial challenges—such as predictive maintenance, quality defect prediction, and process optimization—into scalable AI solutions.

Requirements

  • Education: BS/MS or Ph.D. in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field.
  • Overall Experience: 5+ years of progressive experience in Data Science, utilizing Machine Learning in production to solve complex business problems in a leading role.
  • 3+ years of direct experience applying data science within a manufacturing or industrial environment (ideally automotive).
  • For Senior Level: Demonstrated ownership of services or platform components, end-to-end delivery of machine learning applications.
  • Technical Expertise: Expert proficiency in Python (Numpy, Pandas, Scikit-learn, TensorFlow/PyTorch).
  • Strong SQL skills for complex data extraction, modeling and manipulation.
  • Proven ability to rapidly learn new concepts and apply machine learning methodologies to new and diverse domains.
  • Infrastructure & DevOps: Proficiency with modern software delivery practices ( version control, CI/CD, Terraform ).
  • Familiarity with cloud platforms (GCP Preferred) , cloud-native services, and containerization ( Docker/Kubernetes ).

Nice To Haves

  • Hands-on experience with LLM application concepts (retrieval, grounding, agent design, function/tool use, evaluation, and MCP server).
  • Real-world experience deploying and maintaining production machine learning systems within an industrial or manufacturing set-up.
  • Deep experience with Operational Technology (OT) data infrastructure and industrial protocols (e.g., OPC UA, MQTT).

Responsibilities

  • AI Stack Development: Build features and services across the full AI stack: orchestration, retrieval/grounding, prompt/agent logic, evaluation/guardrails, serving, and observability.
  • End-to-End ML Pipelines: Build end-to-end ML pipelines from data collection and labeling through training, evaluation, and deployment across diverse factory environments.
  • Multi-modal Data Science: Work with diverse, heterogeneous datasets combining multiple modalities including images, multi-spectral sensor outputs, video, text, and tabular data to build scalable solutions.
  • Production Ownership: Take ownership of production models, ensuring robust monitoring, drift detection, and alerting systems for rapid issue resolution.
  • Cross-functional Collaboration: Collaborate with teams in production, process engineering, controls, and quality to translate ambiguous problem statements into actionable, end-to-end machine learning solutions.
  • Manufacturing Problem Solving: Partner with factory, quality and engineering teams to identify high-impact problems solvable through AI.

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.

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What This Job Offers

Job Type

Full-time

Career Level

Senior

Education Level

Ph.D. or professional degree

Number of Employees

5,001-10,000 employees

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