Data Scientist – Product Program Cost Optimization

General Motors • Full-time • United States • 2w ago

Sponsorship: 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., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.)

Hybrid: This position allows flexibility utilizing our hybrid-work appropriately model where team members can work at the GM Global Technical Center requiring the team member to be onsite to support project needs. At GM, we believe work-life harmonization is essential to a team member’s success and job satisfaction

The Role:

The Product Program Cost Optimization (PPCO) team at General Motors is seeking a highly motivated and technically skilled Data Scientist to lead data-driven initiatives that enable product and program-level cost optimization. This role demands a strong foundation in machine learning, deep learning, and generative AI, coupled with advanced proficiency in Python, including object-oriented programming.

The ideal candidate will possess the ability to translate ambiguous business challenges into well-defined scientific problems, design and execute statistical experiments, develop predictive models, and apply data visualization techniques to influence strategic decisions. You will work across functional boundaries, including Engineering, Program Management, R&D, Finance, and Purchasing, to build and deploy intelligent automation tools capable of handling both structured and unstructured data.

As a Data Scientist, you will own the end-to-end lifecycle of AI/ML projects, from problem scoping and exploratory analysis to model development, deployment, and continuous improvement. Your work will directly support GM’s mission to enhance vehicle profitability through data-enabled insights and innovation.

This is a unique opportunity to be part of a high-impact team driving operational efficiency and strategic value across the GM enterprise through advanced analytics and machine intelligence. An advanced degree in a quantitative discipline such as engineering, computer science, mathematics, or statistics is strongly preferred.

What You'll Do:

Develop predictive cost models for automotive components by leveraging deep learning techniques (e.g., Convolutional Neural Networks) on part images and 3D geometry files.
Design and implement Text-to-SQL solutions using state-of-the-art large language models (LLMs) to enable natural language access to complex cost databases.
Automate and optimize existing cost engineering workflows through the development of scalable Python-based automation tools.
Query, integrate, and engineer data from relational databases; establish robust ETL pipelines aimed at building new cost-focused data infrastructure.
Analyze large-scale, heterogeneous business datasets to uncover cost drivers, identify trends, and generate actionable insights.
Build web-based user interfaces and interactive applications to deliver cost analytics solutions and decision support tools to business stakeholders.
Preprocess and transform structured and unstructured data from diverse sources to support downstream machine learning and analytics use cases.
Continuously evaluate, monitor, and maintain the performance of deployed models to ensure sustained accuracy and business value.
Communicate technical findings effectively through clear visualizations, dashboards, and presentations tailored to cross-functional teams.
Develop reusable code frameworks and standardized pipelines to efficiently process various GM supplier forms, including supplier quotes, ED&D breakdowns, and vendor tooling estimates.
Own the end-to-end lifecycle of AI/ML projects, from problem scoping and exploratory analysis to model development, deployment, and continuous improvement.

Your Skills & Abilities (Required Qualifications):

Candidates must be a collaborative team player who will work closely with professionals across the enterprise, including other Cost Engineers, business analysts, and product leads.
Bachelor’s degree in computer science, engineering, statistics, mathematics, physics, or a related field (advanced degree preferred).
5+ years’ experience (3 years with MS) as a data scientist, research scientist, AI analyst, ML engineer, or related role.
Advanced Python proficiency is required.
Expertise across multiple domains of forecasting, clustering, classification, optimization, neural networks, deep learning, natural language processing, LLMs, generative AI, and/or other machine learning and AI methodologies.
Experience with SQL, Databricks, and/or other cloud-based data science platforms.
Strong interpersonal and communication skills and demonstrated working experience with cross-functional product teams.
Experience with data visualization tools (e.g., Tableau, Power BI) to effectively communicate insights.
Solid problem-solving skills and the ability to translate business questions into data-driven solutions.
Familiarity with data storage solutions, databases, and data processing frameworks.
Ability to prioritize and manage multiple tasks and projects at once without sacrificing quality.
Develops solutions in ambiguous situations by leveraging limited data and precedent, applying strategic thinking and deep expertise to address challenges that are new to the organization.
Builds and strengthens relationships with senior internal and external stakeholders who may lack familiarity with the subject matter. Effectively uses data-driven insights to communicate project value, proactively anticipating and resolving concerns or resistance.
Drives change across broader functional areas through influence rather than authority, navigating differing viewpoints, legacy practices, and varied experiences to foster alignment and progress