Data Analytics Specialist Quality Operations - Pontiac MI

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Unless specifically stated otherwise, this role is "On-Site" at the location detailed in the job post.

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt.


We’re turning today’s impossible into tomorrow’s standard — from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.


Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.


The Role

The Lab Quality Engineer is a recognized technical contributor and resource in Engine Dyno Testing. The position requires the ability to address the broadest and most complex problems.  


What You’ll Do

Provide guidance to the engineering team for the instrumentation, equipment and software required for compliant testing
Provide guidance and support to laboratory operations and quality teams to relative to the processes and procedures required to ensure compliant testing
Validate compliance of the measurement instrumentation, diagnostics and calibrations
Validate compliance of the test procedure and data collected for each required test or test sequence
Collaborate with teams to solve problems, improve FTQ
Collaborate with teams to develop tools and processes to improve efficiency
Lead innovation activities in the Quality Department
Complete Quality systems related activities
Train team members on tools and processes
Maintain documents related to Standard Work for projects
Review data and perform statistical analysis
Maintain status of department, projects, and Business Plan Deployment related tasks
Maintain quality reports related to laboratory and operations, issuing monthly reports for status
Perform data acquisition and database management using various PC computer software packages and keep records of status and changes
Refer to the employee training documents maintained and held by the supervisor for specifics as to required job training

Your Skills & Abilities (Required Qualifications)

Bachelors Degree - Engineering degree preferred, other fields of study combined with appropriate experience may be considered
Red X, OPEX, DFSS certifications
Working knowledge of automotive vehicle systems
Knowledge of and application of statistical methods if applying data analysis
Working knowledge of lean engineering / quality systems and strong critical thinking skills
People skills to work effectively with others including global teams and strong oral/written communication skills to effectively interface with GPG leadership

Preferred Skills

3+ years in analytics, data engineering, database development, or predictive modeling; experience with Immuta, Atlan, automotive or operational settings, DFSS, and relevant certifications is a plus. Related platforms such as Tableau, Snowflake, Microsoft Fabric, AWS, Google Cloud, Collibra, and Salesforce are also valued.
Demonstrated experience collecting, integrating, cleaning, reconciling, and validating data, and building, troubleshooting, and optimizing production Databricks pipelines and analytical workloads with advanced SQL, Python/PySpark, Delta Lake, and large datasets; applies testing and version control to maintain reliable code.
Strong predictive analytics expertise, including forecasting and regression; feature preparation, method selection, assumptions, backtesting, holdout validation, leakage prevention, interpretation, and ongoing model monitoring.
Hands-on experience developing, evaluating, and maintaining AI/ML models and agents for data exploration, knowledge retrieval, workflow automation, and decision support, with appropriate access controls and human review.
Expert Power BI skills, including semantic models, DAX, Power Query, dashboards, and Copilot-enabled functionality, alongside practical data governance and stewardship experience across quality, ownership, metadata, lineage, and controlled access.
Ability to partner across engineering, operations, quality, and IT; translate needs into measurable analytical outcomes; troubleshoot system and data issues; build or support applications, APIs, workflow tools, and integrations for operational users; support documentation, data planning, migration, and architecture; and manage delivery in Jira Cloud.