Data Scientist at General Motors in Warren, MI
- Company: General Motors
- Location: Warren, Michigan, United States of America
- Job type: full time
- Workplace: hybrid
- Posted: 2026-10-14
All open roles at General Motors
Job description
Job Description The Role As an L6 Data Scientist supporting Sales, Brand & Dealer, you will lead the execution of one or more workstreams within an AI, machine learning, or data science product. You will build deep technical expertise under the guidance of the product’s lead scientist while actively contributing to product decisions, methodological direction, and the development of high-impact solutions. What You Will Do Lead the execution of assigned AI, machine learning, or data science workstreams from methodology through delivery. Contribute to product decisions and help shape the ideation, design, and development of analytical methods and solutions. Develop high-quality code that is methodologically sound, maintainable, scalable, and operationally robust. Explore and apply new methods, technologies, and approaches to expand the product’s technical capabilities. Deliver results on time while managing risks and maintaining methodological and operational quality. Partner cross-functionally with data engineering, software delivery, product delivery teams, business units, and other stakeholders to drive product development and business outcomes. Translate complex technical concepts, tradeoffs, assumptions, and risks into clear insights and recommendations for stakeholders and leaders. Present workstream progress, findings, and business impact to technical and business audiences. Your Skills and Abilities (Required Qualifications) 3+ years working in the field of advanced analytics, AI/ML and/or operations research initiatives, developing and integrating analytical methods into software products; Demonstrated use of innovative methodologies and approaches to solving business problems, resulting in meaningful business impact; Experience across multiple AI/ML and analytics domains (LLMs, forecasting, deep learning, operations research, prescriptive & predictive methods, etc.); 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. Strong presentation and communication skills; and M.S. or Ph.D. in operations research, engineering, computer science, applied statistics, economics, physics, or related field. Equivalent additional experience may substitute for advanced degree. What Can Give You a Competitive Advantage (Preferred Qualifications) Experience contributing to AI, machine learning, or data science products from concept through production delivery. Experience influencing product decisions and shaping methodological direction. Breadth across modern data science methods, tools, and technologies, with a demonstrated interest in continuous technical growth. Experience building solutions that are reliable, maintainable, scalable, and operationally ready. Experience working across multidisciplinary teams, including data engineering, software engineering, product delivery, and business stakeholders. Demonstrated ability to connect technical work to measurable business impact. Publications, conference talks, patents or other generated intellectual property, committed open-source work, or other external technical recognition preferred. Experience presenting complex analytical results and technical tradeoffs to senior leaders and diverse audiences. #LI-KL2 

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 di
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