Staff Data Scientist - AI Engineering & Productivity

Location: Austin, Texas, United States of America, Warren, Michigan, United States of America

Remote Type: Hybrid

Time Type: Full time

Job Description

Job Description

The Role

The AI Engineering and Productivity team in the Global Planning, Design, and Product IT organization is looking for a Staff Data Scientist to propel our mission of empowering Engineering teams by delivering reliable and secure AI-driven tools that streamline workflows, accelerate decision making, surface actionable insights, and unlock measurable productivity gains across the product lifecycle.

As a Staff Data Scientist, you will be responsible for leading one or more AI/ML and data science products, while also contributing highly technical work on problems of significant complexity. You will be accountable for translating ambiguous Engineering business challenges into scalable, production-grade AI products that deliver measurable enterprise impact.

What You’ll Do

• Shape scientific direction, and ensure methodological quality and operational robustness used across the suite of products that you are responsible for.
• Grow the technical capabilities of the scientist community within the AI Engineering and Productivity organization through exploration of new methods and technologies, cross-functional knowledge sharing, mentorship, internal reviews, and establishment of reusable methods and frameworks.
• Drive results on time and within budget, managing risks, and ensuring methodological and operational quality across products that you oversee to generate significant and measurable business impact.
• Work cross-functionally across data engineering, delivery teams, software delivery, other business units and beyond to drive product development, management and results; and
• Influence stakeholders and leaders by translating technical tradeoffs, risks and opportunities into clear business decisions.

Your Skills & Abilities (Required 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, etc.), with a preferred focus on LLMs.
• Expertise in Python and other cloud-based data science platforms (Databricks preferred), and proficiency in SQL;
• Experience with generative AI tools and platforms such as Cursor, GitHub and/or Microsoft Copilot, Glean, Databricks Genie, etc.
• Demonstrated 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. 

What Can Give You a Competitive Advantage (Preferred Qualifications)

• 10+ years working with and 6+ years leading advanced analytics, AI/ML and/or operations research initiatives.
• Ph.D. in operations research, engineering, computer science, applied statistics, physics, or related field.
• Demonstrated ability to lead multi-team member initiatives using novel methods resulting in substantial business impact.
• Publications, conference talks, patents or other generated intellectual property, committed open-source work, or other external technical recognition preferred.

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc). This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. Relocation benefits are available for candidates who qualify under company policy.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us 

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. 

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

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