Top Data & Analytics Jobs

The Senior Prognostics Data Engineer will design and deploy advanced signal processing methods for prognostics applications, conduct failure mode analysis, analyze sensor data using statistical techniques, develop health monitoring models, and optimize algorithms while collaborating with cross-functional teams to deliver high-quality prognostics solutions.

As a Senior Data Engineer, you will develop analytics-driven solutions for GM organizations, build analytical datasets, collaborate with Researchers and Data Scientists, automate data processes, and adopt cloud-first technologies. The role emphasizes the use of data engineering best practices while fostering a culture of continuous learning within the team.

Develop, test, and create quality solutions as an Electrical/Electronics Quality Engineer. Responsible for defect analysis, problem-solving, and communication with Quality management. Lead cross-functional processes, root cause analysis, and countermeasure execution. Assist in warranty reviews, investigations, and problem-solving to improve quality standards. Skills required include Excel, Power BI, intermediate English, and experience in manufacturing environments.

As a Senior Data Engineer, you will design, build, and maintain data collection systems, ensuring data quality and integrity. You'll manage data configurations, optimize collection methods, and implement process improvements while working with big data technologies. Strong programming skills in Python and experience in vehicle communication networks are required.

The Staff Data Scientist will develop advanced marketing models, integrating data sources for precision targeting, and providing insights to enhance marketing strategies. Responsibilities include statistical modeling, data preprocessing, and visualizing data for diverse stakeholders, all aimed at driving sales and consumer engagement in an evolving market focused on electric vehicles.

The AI Center Technical Manager will lead a team of ML engineers, focusing on AI model deployment and operationalization. Responsibilities include developing frameworks for AI operations, overseeing the deployment of ML solutions, ensuring code quality through DevSecOps, and collaborating with data engineers and scientists. The role requires hands-on coding and leadership to foster team growth and innovative AI practices.