Manager, Yield Management - GTM AA Data Scientist

July 16, 2026

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About the 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.

Responsibilities

Guide, mentor, and support a team of 4–6 AI/ML engineers and data scientists, overseeing daily standups, sprint planning, and code reviews.
Lead the hands-on development, testing, and deployment of predictive models, time-series forecasting, and optimization algorithms.
Directly oversee the development, maintenance, and refinement of demand sensing algorithms to support sales and operations planning (S&OP) and optimize yield.
Drive the practical integration and deployment of Agentic AI solutions to automate complex workflows and operational processes.
Ensure the team builds robust, automated pipelines for data ingestion, model training, deployment, monitoring, and retraining in production environments.
Establish and enforce best practices for clean code, model versioning, comprehensive documentation, and system scalability.
Maintain rigorous standards for data integrity and model validation, ensuring all solutions adhere to ethical and responsible AI guidelines.
Partner with product managers, software engineers, and business analysts to translate functional requirements into technical specifications.
Manage project timelines, unblock technical hurdles, and regularly communicate project status and technical milestones to the Senior Manager.

Requirements

Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or a related quantitative field.
6–8+ years of progressive experience in AI/ML engineering or data science, with at least 1–3 years of experience formally leading or managing technical team members.
Exceptional proficiency in Python and deep familiarity with ML/DL libraries (e.g., PyTorch, TensorFlow, scikit-learn) and SQL.
Proven experience deploying and maintaining ML models in production cloud environments (AWS, Azure, or GCP).
Strong command of MLOps tools, version control (Git), and containerization technologies (e.g., Docker, Kubernetes).
Hands-on experience or strong conceptual understanding of Agentic AI frameworks and Large Language Model (LLM) orchestration.

Nice-to-haves

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.
Experience with distributed computing frameworks (e.g., Spark) for large-scale data processing.

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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