Sr. Manager, Yield Management - GTM Advanced Analytics

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, we are seeking a visionary and experienced Senior Manager to lead the strategic development, deployment, and continuous enhancement of cutting‑edge AI/ML solutions for Yield Management. In this pivotal role, you will lead a high‑performing team to transform business processes through predictive demand forecasting, dynamic segmentation, sensitivity analysis, and optimization algorithms. The ideal candidate blends deep technical expertise in AI/ML engineering with a proven track record of delivering end‑to‑end production‑grade AI solutions that drive measurable business impact.

• Strategic AI/ML Leadership & Delivery
  • End‑to‑End Lifecycle Management: lead the design, validation, deployment, and monitoring of production‑grade AI/ML solutions (e.g., predictive modeling, forecasting, optimization, and segmentation).
  • Demand Sensing & S&OP: lead development, maintenance, and optimization of advanced demand sensing algorithms to support sales and operations planning (S&OP) and yield management.
  • Roadmap & Innovation: drive the strategic AI/ML roadmap, identifying innovative use cases—including Agentic AI for workflow automation—to deliver significant business value.
  • Rapid Prototyping: foster a culture of rapid prototyping and rigorous testing to quickly validate the business utility of new AI/ML applications.
• Technology Strategy & MLOps Excellence
  • Tech Stack Evolution: evaluate and adopt emerging AI/ML platforms, frameworks, and methodologies to enhance solution efficiency, scalability, and performance.
  • MLOps & Governance: establish and enforce robust MLOps practices, model governance, version control, and comprehensive documentation to ensure seamless deployment and retraining.
  • Responsible AI: champion ethical AI principles, ensuring fairness, transparency, and data privacy are embedded across the model lifecycle.
  • Data Quality: oversee data management practices (sourcing, cleaning, preprocessing) to ensure high‑quality data pipelines for all AI/ML models.
• Cross‑Functional Collaboration & Stakeholder Engagement
  • Strategic Alignment: act as the primary liaison between technical teams and business stakeholders (Sales & Marketing, Finance, IT) to align AI/ML initiatives with corporate strategy.
  • Executive Communication: translate complex algorithmic concepts and technical outcomes into clear, actionable insights and recommendations for executive leadership.
  • People Leadership: guide and mentor data scientists and AI/ML engineers in technical execution, professional growth, and stakeholder management.

• Master’s in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or a closely related quantitative field.
• 10+ years of progressive experience in AI/ML engineering or data science, with 3–5 years of experience directly leading and managing technical teams.
• Proven experience building and deploying production‑grade predictive models, time‑series forecasting, and optimization algorithms.
• Hands‑on experience building and deploying Agentic AI solutions for complex workflow automation.
• Advanced proficiency in Python and core ML libraries (e.g., PyTorch, Tensor Flow, scikit‑learn). Strong command of SQL.
• Proven experience deploying and managing AI/ML workloads on cloud platforms (AWS, Azure, or GCP) using MLOps tools.
• Experience developing user‑facing applications or dashboards (e.g., Streamlit, Dash, Flask/Django) for model consumption.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or a closely related quantitative field.
• Prior management consulting experience and/or extensive experience collaborating with third‑party consulting teams to deliver strategic projects.
• Direct experience in Yield Management, Revenue Management, Supply Chain, or S&OP within the automotive, manufacturing, or related industries.
• Familiarity with…