Cost-Driven AI/ML Data Scientist

General Motors; Warren (MI); Hybrid; USD 120,000 - 160,000; Full time

Job summary

General Motors is seeking a Data Scientist to join the Product Program Cost Optimization AI/ML Solutions team. You will translate cost-related problems into scalable technical solutions, owning the full product lifecycle from data prep to deployment.

Join a team building production-grade data products, predictive models, and AI capabilities to improve cost intelligence and support product decisions in a hybrid work environment.

Qualifications

• Bachelor’s degree in computer science, data science, or quantitative field.
• Five+ years in data science/ML or related role.
• Strong Python and SQL skills; production-grade code.

Responsibilities

• Partner with engineering, cost engineering, purchasing, finance, program management, and stakeholders to define problems and delivery priorities.
• Develop predictive and statistical models for cost estimation, forecasting, and decision support.
• Build data pipelines integrating engineering, purchasing, supplier, manufacturing, and financial data.
• Create reusable Python frameworks, automation, and data-processing patterns for complex data.
• Develop analytical apps, APIs, dashboards, and visualizations to inform business decisions.
• Apply ML, LLMs, retrieval-augmented generation, tool calling, and AI agents to create business value.

Skills

Python

SQL

Data pipelines

ML engineering

Databricks

CI/CD

MLOps

API/ dashboards

English communication

Education

Bachelor's degree in CS/Math/Engineering

Master's degree (preferred)

Tools

FastAPI/ Flask/ Dash/ Streamlit

Power BI/Tableau/Plotly

Job description

General Motors is seeking a Data Scientist to join the Product Program Cost Optimization AI/ML Solutions team. You will translate cost-related problems into scalable technical solutions, owning the full product lifecycle from data prep to deployment.

Join a team building production-grade data products, predictive models, and AI capabilities to improve cost intelligence and support product decisions in a hybrid work environment.