Cost Engineer – Data Analytics

The Program and Purchase Cost Optimization (PPCO) team at General Motors is seeking a highly motivated individual for the role of Cost Engineer – Data Analytics.  This individual will be technically skilled in Data Analytics, with the ability to lead initiatives that enable product and program level cost optimization through robust data engineering, exploratory data analysis (EDA), and predictive modeling. This role sits within the PPCO Systems and Data Analytics teams and focuses on building and maintaining the data foundations that power cost analytics initiatives across GM Finance. You will work with data from across the GM ecosystem, identifying interconnections between multiple enterprise applications from different functional areas (e.g., engineering, purchasing, finance, program management) and designing scalable data structures and pipelines that turn disparate and unstructured data into trusted, analysis-ready assets. The ideal candidate has deep experience in data engineering, ETL/ELT, database and table management, and EDA, combined with strong skills in classical predictive modeling. You will use current data to understand behaviors and to predict product attributes such as manufacturing parameters, product cost, program development cost creep, and economic factors based on parameters and features extracted from existing data. You will partner closely with Data Analysts, AI Analysts, IT, and cross-functional stakeholders to design and implement data architectures, curate high-quality datasets, and develop predictive models that deliver meaningful, actionable insights to improve vehicle profitability and program performance.