Sr. Manager, Yield Management - GTM Advanced Analytics

Job Summary

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.

What You'll Do

• 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 the 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
  • Technology 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.

Qualifications

• 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, TensorFlow, 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.

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

Pay

This position is leadership level 5 and ranges from $141,700-$268,300.

Schedule

This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week.