Data Scientist - AI/ML Solutions PPCO

The Role General Motors is seeking a Data Scientist to join the Product Program Cost Optimization AI/ML Solutions team. This role develops and scales production-grade data products, predictive models, and AI capabilities that improve cost intelligence and support product and program decisions. The Data Scientist will translate ambiguous cost, engineering, purchasing, and finance problems into scalable technical solutions. They will own work across the full product lifecycle: problem definition, data preparation, modeling, application development, deployment, monitoring, support, and continuous improvement. This role requires demonstrated depth in production machine learning, data engineering, and modern AI applications. The successful candidate will build governed capabilities that convert complex engineering, supplier, manufacturing, and financial data into measurable improvements in cost decisions, speed, quality, and adoption. What You Will Do •    Partner with Engineering, Cost Engineering, Purchasing, Finance, Program Management, R&D, and business stakeholders to define problems, success measures, product requirements, and delivery priorities. •    Develop predictive and statistical models for part-cost estimation, cost-driver analysis, forecasting, classification, optimization, and decision support. •    Build and maintain production-grade data pipelines integrating engineering, purchasing, supplier, manufacturing, and financial data. •    Develop reusable Python frameworks, automation, and data-processing patterns for complex structured and unstructured data. •    Build user-facing analytical applications, APIs, dashboards, and visualizations that turn model outputs into business decisions. •    Develop AI capabilities for natural-language access to cost data, supplier quote and document processing, engineering workflow automation, and decision support. •    Apply machine learning, large language models, retrieval-augmented generation, tool calling, structured outputs, and AI agents where they create measurable business value. •    Develop and evaluate multimodal solutions that may use images, engineering files, 3D geometry, documents, and relational data to support cost-estimation and cost-engineering use cases. •    Establish data-quality controls, model-evaluation methods, documentation, and monitoring required for reliable production use. •    Use Git, automated testing, CI/CD, MLOps, and model deployment practices to create maintainable, reproducible, and governed solutions. •    Communicate technical findings, limitations, recommendations, and business value to technical and non-technical audiences. •    Work within GM requirements for data protection, responsible AI, security, governance, and model risk management. •    Influence stakeholders through data, technical credibility, and clear product thinking, including in situations with incomplete data or limited precedent. Required Qualifications •    Bachelor’s degree in computer science, data science, engineering, statistics, mathematics, operations research, physics, or a related quantitative discipline. •    Five or more years of relevant experience, or three or more years with a related master’s degree, in data science, machine learning, ML engineering, data engineering, applied analytics, or a related role. •    Advanced Python proficiency, including experience developing modular, testable, maintainable, and production-quality code. •    Strong SQL skills, including designing, querying, integrating, and optimizing relational data. •    Demonstrated experience building scalable data pipelines, transforming large datasets, and establishing data-quality controls. •    Demonstrated experience deploying and supporting analytical or machine-learning products in production, beyond experimentation or proof of concept. •    Applied experience with