Staff Data Scientist — AI & Engineering Productivity

General Motors; Warren (MI); Hybrid; USD 150,000 - 190,000; Full time

Job summary

General Motors seeks a Staff Data Scientist to lead AI/ML products, translate complex engineering problems into scalable AI solutions, and deliver measurable enterprise impact across the product lifecycle.

You will shape scientific direction, mentor the scientist community, and drive cross-functional collaboration to ensure robust, production-ready results with strong communication to stakeholders.

Qualifications

• 8+ years working with and 3+ years leading advanced analytics, AI/ML and/or operations research initiatives.
• Demonstrated thought leadership surrounding use of innovative methodologies and approaches to solving business problems.
• Deep expertise across multiple AI/ML and analytics domains (LLMs, forecasting, deep learning, operations research, prescriptive & predictive methods).

Responsibilities

• Shape scientific direction and ensure methodological quality across products you oversee.
• Grow scientist capabilities through new methods, knowledge sharing, mentorship, and reusable frameworks.
• Drive results on time and within budget, managing risks and delivering measurable business impact.
• Collaborate across data engineering, delivery teams, software delivery and other units to drive product development.
• Influence stakeholders by translating technical tradeoffs, risks and opportunities into clear business decisions.

Skills

AI/ML

Lead analytics

Python

SQL

Databricks

LLMs

Forecasting

Communication

Operations research

Education

M.S. degree in operations research / engineering / CS / applied statistics / physics

Ph.D. in related field

Tools

Databricks

Cursor

GitHub

Microsoft Copilot

Glean

Databricks Genie

Job description

General Motors seeks a Staff Data Scientist to lead AI/ML products, translate complex engineering problems into scalable AI solutions, and deliver measurable enterprise impact across the product lifecycle.

You will shape scientific direction, mentor the scientist community, and drive cross-functional collaboration to ensure robust, production-ready results with strong communication to stakeholders.