The Global Engineering Operations & Specifications Analytics team is driving transformation in how General Motors approaches vehicle engineering through advanced data science. We combine deep knowledge of GM’s engineering systems, processes, and data with cutting-edge analytics to deliver solutions that improve efficiency and decision-making across the organization.
The Role
As a Data Scientist , you will collaborate with cross-functional teams to design and implement high-impact, data-driven solutions that address complex engineering challenges. Your work will involve framing stakeholder problems, building data pipelines, developing AI/ML models, and creating user interfaces that enable actionable insights for decision support.
What You’ll Do
- Partner with engineering teams to identify opportunities and deliver data-driven solutions.
- Apply advanced data science and modeling techniques to solve complex problems:
- Build predictive and prescriptive models and machine-learning algorithms.
- Analyze large, diverse datasets to uncover trends and patterns.
- Preprocess structured and unstructured data for modeling.
- Monitor and maintain model performance.
- Develop intuitive data visualizations and dashboards to communicate insights effectively.
- Create scalable, repeatable code and processes to improve efficiency.
- Collaborate with technical teams to deliver analytical datasets and user interfaces aligned with business needs.
- Document models, processes, and technical workflows for transparency and reproducibility.
Required Qualifications
- Bachelor’s degree in Data Science, Analytics, Operations Research, Engineering, Statistics, Economics, Computer Science, Applied Mathematics, or a related quantitative field.
- Minimum 1 year of experience as a Data Scientist, including developing, deploying, and monitoring large analytic datasets and machine-learning models.
- Proficiency in:
- Programming: Python or similar languages.
- Data Querying: SQL, Spark, or similar.
- Visualization Tools: Power BI, Tableau, or similar.
- Data Platforms: Databricks or similar data lake technologies.
- Strong ability to work with diverse technical teams and manage multiple projects simultaneously.
- Excellent communication, collaboration, and problem-solving skills.
- Ability to synthesize complex data into actionable business insights.
Preferred Qualifications
- Domain knowledge of engineering processes and data (e.g., part release, change management, issue resolution, validation).
- Experience building web applications using frameworks like Dash or Streamlit.
- Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
