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Manager, Yield Management - GTM AA Data Scientist

Job in Dearborn, Wayne County, Michigan, 48120, USA
Listing for: Ford Motor Company
Full Time position
Listed on 2026-06-19
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Engineering, Data Science Manager
Job Description & How to Apply Below
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.

In this position...

Reporting to the Senior Manager, AI/ML Solutions, you will lead a high-performing team of data scientists and AI/ML engineers to design, build, and deploy production-grade AI/ML models. In this hands-on leadership role, you will bridge the gap between technical execution and strategic goals, driving the development of advanced algorithms for predictive demand forecasting, dynamic segmentation, and yield optimization. You will ensure technical excellence, robust MLOps practices, and the timely delivery of scalable AI solutions.

Reporting to the Senior Manager, AI/ML Solutions, you will lead a team of data scientists and engineers to build and deploy production-grade AI/ML models. In this hands-on role, you will bridge technical execution and strategy, driving advanced solutions for forecasting, segmentation, and yield optimization while ensuring technical excellence and robust MLOps.

What you'll do...

Technical Execution & Team Leadership

Hands-on Team Leadership:
Guide, mentor, and support a team of 4-6 AI/ML engineers and data scientists, overseeing daily standups, sprint planning, and code reviews.

Model Development & Deployment:
Lead the hands-on development, testing, and deployment of predictive models, time-series forecasting, and optimization algorithms.

Demand Sensing & S&OP:
Directly oversee the development, maintenance, and refinement of demand sensing algorithms to support sales and operations planning (S&OP) and optimize yield.

Agentic AI Implementation:
Drive the practical integration and deployment of Agentic AI solutions to automate complex workflows and operational processes.

MLOps, Quality & Governance

MLOps & Pipelines:
Ensure the team builds robust, automated pipelines for data ingestion, model training, deployment, monitoring, and retraining in production environments.

Code & Architecture Standards:
Establish and enforce best practices for clean code, model versioning, comprehensive documentation, and system scalability.

Responsible AI & Data Quality:
Maintain rigorous standards for data integrity and model validation, ensuring all solutions adhere to ethical and responsible AI guidelines.

Collaboration & Project Management

Cross-Functional Delivery:
Partner with product managers, software engineers, and business analysts to translate functional requirements into technical specifications.

Progress Tracking:
Manage project timelines, unblock technical hurdles, and regularly communicate project status and technical milestones to the Senior Manager.

What you'll do...

Technical Execution & Team Leadership

Hands-on Team Leadership:
Guide, mentor, and support a team of 4-6 AI/ML engineers and data scientists, overseeing daily standups, sprint planning, and code reviews.

Model Development & Deployment:
Lead the hands-on development, testing, and deployment of predictive models, time-series forecasting, and optimization algorithms.

Demand Sensing & S&OP:
Directly oversee the development, maintenance, and refinement of demand sensing algorithms to support sales and operations planning (S&OP) and optimize yield.

Agentic AI Implementation:
Drive the practical integration and deployment of Agentic AI solutions to automate complex workflows and operational processes.

MLOps, Quality & Governance

MLOps & Pipelines:
Ensure the team builds robust, automated pipelines for data ingestion, model training, deployment, monitoring, and retraining in production environments.

Code & Architecture Standards:
Establish and enforce best practices for clean code, model versioning, comprehensive documentation, and system scalability.

Responsible AI & Data Quality:
Maintain rigorous standards for data integrity and model validation, ensuring all solutions adhere to ethical and responsible AI guidelines.

Collaboration & Project Management

Cross-Functional Delivery:
Partner with product managers, software engineers, and business analysts to translate functional requirements into technical specifications.

Progress Tracking:
Manage project timelines, unblock technical hurdles, and regularly communicate project status and technical milestones to the Senior Manager.
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