Data Scientist AIML Solutions PPCO

Job Description

The Role
General Motors is seeking a Data Scientist to join the Product Program Cost Optimization AI/ML Solutions team. This role develops and scales production-grade data products predictive models and AI capabilities that improve cost intelligence and support product and program decisions.
The Data Scientist will translate ambiguous cost engineering purchasing and finance problems into scalable technical solutions. They will own work across the full product lifecycle: problem definition data preparation modeling application development deployment monitoring support and continuous improvement.
This role requires demonstrated depth in production machine learning data engineering and modern AI applications. The successful candidate will build governed capabilities that convert complex engineering supplier manufacturing and financial data into measurable improvements in cost decisions speed quality and adoption.

What You Will Do
Partner with Engineering Cost Engineering Purchasing Finance Program Management R&D and business stakeholders to define problems success measures product requirements and delivery priorities.
Develop predictive and statistical models for part-cost estimation cost-driver analysis forecasting classification optimization and decision support.
Build and maintain production-grade data pipelines integrating engineering purchasing supplier manufacturing and financial data.
Develop reusable Python frameworks automation and data-processing patterns for complex structured and unstructured data.
Build user-facing analytical applications APIs dashboards and visualizations that turn model outputs into business decisions.
Develop AI capabilities for natural-language access to cost data supplier quote and document processing engineering workflow automation and decision support.
Apply machine learning large language models retrieval-augmented generation tool calling structured outputs and AI agents where they create measurable business value.
Develop and evaluate multimodal solutions that may use images engineering files 3D geometry documents and relational data to support cost-estimation and cost-engineering use cases.
Establish data-quality controls model-evaluation methods documentation and monitoring required for reliable production use.
Use Git automated testing CI/CD MLOps and model deployment practices to create maintainable reproducible and governed solutions.
Communicate technical findings limitations recommendations and business value to technical and non-technical audiences.
Work within GM requirements for data protection responsible AI security governance and model risk management.
Influence stakeholders through data technical credibility and clear product thinking including in situations with incomplete data or limited precedent.

Required Qualifications
Bachelors degree in computer science data science engineering statistics mathematics operations research physics or a related quantitative discipline.
Five or more years of relevant experience or three or more years with a related masters degree in data science machine learning ML engineering data engineering applied analytics or a related role.
Advanced Python proficiency including experience developing modular testable maintainable and production-quality code.
Strong SQL skills including designing querying integrating and optimizing relational data.
Demonstrated experience building scalable data pipelines transforming large datasets and establishing data-quality controls.
Demonstrated experience deploying and supporting analytical or machine-learning products in production beyond experimentation or proof of concept.
Applied experience with multiple machine-learning methods including regression classification clustering forecasting optimization neural networks natural language processing generative AI or related methods.
Experience with Databricks or another modern cloud-based data and machine-learning platform.
Experience with version control automated testing CI/CD model evaluation deployment monitoring and reproducible development practices.
Experience building solutions that use both structured and unstructured enterprise data.
Demonstrated depth in at least two of the following areas:
o Predictive cost modeling forecasting optimization or decision science
o Large language model applications including retrieval-augmented generation tool calling structured outputs or evaluation frameworks
o Document intelligence information extraction or supplier quote and cost-breakdown processing
o Multimodal machine learning using images engineering files or 3D geometry
o Scalable data engineering and production ML platforms
Experience building analytical applications APIs dashboards or visualization solutions using tools such as FastAPI Flask Dash Streamlit Power BI Tableau Plotly or similar frameworks.
Ability to translate business questions into data product and modeling requirements.
Demonstrated ability to work effectively across product engineering finance purchasing and business teams.
Ability to manage multiple priorities and deliver high-quality work in ambiguous situations.
Clear written and verbal communication skills.

Preferred Qualifications
Masters degree or higher in a related quantitative discipline.
Experience in automotive engineering product development purchasing supply chain manufacturing finance or cost engineering.
Experience developing cost-estimation should-cost profitability sourcing supplier-risk or financial-risk models.
Experience with part-image analysis computer vision 3D geometry CAD-related data or engineering file processing.
Experience developing Text-to-SQL or natural-language interfaces to enterprise data.
Experience processing supplier quotes ED&D breakdowns vendor tooling estimates technical documents or other cost-engineering artifacts.
Experience with PySpark Delta Lake MLflow Databricks Workflows Databricks Asset Bundles or related platform capabilities.
Demonstrated ability to connect technical delivery to measurable cost efficiency adoption or decision-quality outcomes.

#LI-HP2

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. This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.

About GM

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Why Join Us

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Benefits Overview

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