Staff Data Scientist – AI Engineering, Productivity

General Motors

. Lead one or more AI/ML and data science products .

Posted 10/9/2026full-timeUnited StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading AI/ML and data science products, with a focus on delivering scalable, production-grade solutions. Proficient in translating complex business challenges into actionable insights while fostering technical growth within teams.

Highest-signal resume keywords

AI/ML Product LeadershipDeep Learning ExpertisePython ProficiencySQL ProficiencyGenerative AI Tools Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Advanced AnalyticsOperations ResearchForecastingPredictive MethodsPrescriptive MethodsLLMs ExpertiseData Science MethodologiesAnalytical Strategy DevelopmentTechnical Tradeoff AnalysisRisk Management

Soft Skills

Strong Presentation SkillsEffective Communication

Tools & Technologies

DatabricksCursorGitHubMicrosoft CopilotGleanDatabricks Genie

Industry Keywords

AI ProductsData ScienceTechnical LeadershipMethodological QualityOperational Robustness

Tech Stack

Tools & technologies

CloudPythonSQL

About the role

Key responsibilities & impact

Lead one or more AI/ML and data science products
Contribute highly technical work on complex problems
Translate ambiguous Engineering business challenges into scalable, production-grade AI products
Deliver reliable and secure AI-driven tools that streamline workflows, accelerate decision-making, surface actionable insights, and improve productivity across the product lifecycle
Shape scientific direction and ensure methodological quality and operational robustness across assigned products
Grow technical capabilities within the scientist community through new methods, knowledge sharing, mentorship, internal reviews, and reusable frameworks
Drive results on time and within budget while managing risks and ensuring quality
Work cross-functionally with data engineering, delivery teams, software delivery, other business units, and additional stakeholders
Influence stakeholders and leaders by translating technical tradeoffs, risks, and opportunities into business decisions

Requirements

What you’ll need

8+ years working with advanced analytics, AI/ML and/or operations research initiatives
3+ years leading advanced analytics, AI/ML and/or operations research initiatives
Demonstrated thought leadership using innovative methodologies and approaches to solve business problems
Deep expertise across multiple AI/ML and analytics domains, including LLMs, forecasting, deep learning, operations research, and prescriptive and predictive methods; preferred focus on LLMs
Expertise in Python and cloud-based data science platforms; Databricks preferred
Proficiency in SQL
Experience with generative AI tools and platforms such as Cursor, GitHub, Microsoft Copilot, Glean, and Databricks Genie
Ability to frame ambiguous, high-value business problems into tractable analytical strategies and measurable outcomes
Strong presentation and communication skills
M.S. degree in operations research, engineering, computer science, applied statistics, physics, or related field
Equivalent additional experience may substitute for an advanced degree
No GM immigration-related sponsorship is provided; applicants must not require sponsorship now or in the future, including H-1B, OPT, STEM OPT, CPT, TN, or J-1 support

Benefits

Comp & perks

Hybrid work arrangement with reporting to a specific location at least 3 times a week (or frequency dictated by manager)
Relocation benefits for candidates who qualify under company policy
GM employee well-being and total rewards benefits; specific benefits are not enumerated in the posting
Reasonable accommodation support for applicants with disabilities