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# Data Scientist

- **Company:** General Motors
- **Location:** Austin, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Cloud Database, Information Engineering, Cursor (Graphical User Interface Elements), Github, Python (Programming Language), Machine Learning, Open Source Technology, Software Engineering, SQL Databases, Microsoft Power Automate, Large Language Models, Deep Learning, Generative AI, Information Technology, Databricks
- **Published:** August 28, 2026
- **Apply:** https://www.austinjobsite.com/job.asp?id=3367880903&tx=KL1717FFG&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 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.

## Description

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.


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