IT Operations Analyst

GM • Warren, MI

16h • Hybrid

About The Position

General Motors is seeking a detail-oriented, data-driven IT Operations Analyst to support and modernize operations for business-critical applications across dealer operations, vehicle engineering, finance, purchasing, supply chain, and other business functions. The role combines IT operations, data analysis, statistical methods, intelligent automation, and emerging technologies to identify operational patterns, reduce repetitive manual work, and improve application-support reliability and efficiency. Prior professional IT Operations experience is not required; relevant coursework, projects, internships, certifications, research, and other practical experience may provide a foundation for success.

The analyst supports application stability, reliability, and accuracy through operational monitoring, incident triage, data validation, reporting, release verification, and application-health assessment. The role includes examining operational data and using approved generative and Agentic AI tools, statistical methods, and automation to improve repeatable workflows. The analyst works with application engineers, database administrators, infrastructure teams, business analysts, and business stakeholders. Complex technical issues are escalated to engineering or subject-matter experts as the analyst develops knowledge of enterprise applications and production operations.

This is a hybrid role. The successful candidate is expected to report to either Austin, Texas, or Warren, Michigan, three days per week (Tuesday through Thursday). The role may require non-traditional hours or night shifts when needed. GM does not provide immigration-related sponsorship for this role.

Requirements

• Bachelor's degree in Information Systems, Computer Science, Information Technology, Engineering, Data Science, Statistics, Economics, Econometrics, Finance, Mathematics, Business Analytics, or a related technical, quantitative, or business field.
• Strong quantitative and problem-solving foundation, including the ability to interpret data and identify patterns, trends, anomalies, relationships, and improvement opportunities.
• Coursework, academic projects, internships, certifications, or practical exposure involving SQL, Python, R, PowerShell, Shell/Bash, or comparable programming, scripting, statistical, or data tools.
• Exposure to generative AI, Agentic AI, prompt engineering, machine learning, or workflow automation through coursework, projects, certifications, internships, independent learning, or practical application.
• Familiarity with statistical methods, forecasting, data interpretation, or other quantitative methods used to investigate problems and support data-driven decisions.
• Familiarity with reporting or visualization tools such as Power BI, Tableau, Excel, Power Query, or comparable platforms.
• Ability to synthesize information from multiple sources and translate findings into clear insights, recommendations, dashboards, reports, or actions.
• Strong problem-solving, organizational, written, and verbal communication skills, and ability to learn unfamiliar technologies and business processes quickly.
• Ability to collaborate effectively with technical and business teams and willingness to learn enterprise applications, IT Operations, monitoring, incident management, and production-support practices.
• Strong attention to detail and commitment to data quality, accuracy, responsible AI use, and appropriate information protection.
• Willingness to support production operations and work non-traditional hours or night shifts when required.
• Prior professional IT Operations experience is not required.

Nice To Haves

• Coursework, projects, internships, certifications, or research involving data analytics, statistics, forecasting, machine learning, emerging technologies, automation, or quantitative methods.
• Experience using Python, SQL, R, Power BI, Tableau, Excel, Power Query, or PowerShell through academic, internship, certification, research, or personal projects.
• Experience creating dashboards, quantitative models, forecasts, automated reports, AI agents, or automated workflows.
• Exposure to Agentic AI, prompt engineering, AI-assisted data exploration, or business-process automation, including validation of AI-generated outputs and responsible-use practices.
• Familiarity with business processes and applications, and interest in how technology, data, and operational workflows support functions such as finance, engineering, purchasing, supply chain, and dealer operations.
• Exposure to Windows, Linux, databases, cloud technologies, APIs, application monitoring, observability, or other enterprise technology environments.
• Strong interest in applying data, statistical methods, intelligent automation, and emerging technologies to IT Operations to identify patterns, reduce repetitive work, improve decision-making, and increase operational reliability and efficiency.

Responsibilities

• Support and monitor business-critical applications and operational processes across multiple business units using alerts, logs, dashboards, job results, reports, and system metrics.
• Triage incidents, conduct initial investigations, apply documented procedures or workarounds, and escalate complex issues with clear supporting information.
• Analyze operational data such as incident volumes, error rates, response and resolution times, application availability, service-level performance, MTTR, and MTTD using statistical methods, trend identification, forecasting, and other quantitative techniques.
• Use SQL, Python, R, PowerShell, Shell/Bash, or comparable tools to investigate issues, validate information, work with data, and automate repeatable operational activities.
• Use approved generative and Agentic AI tools to develop or improve workflows for incident triage, diagnostics, information retrieval, health checks, reporting, documentation, data validation, and other repeatable processes.
• Partner with business and technology stakeholders to identify operational pain points and opportunities for data, intelligent automation, and process improvements.
• Build dashboards, operational metrics, reports, and automated reporting using Power BI, Python, Excel, Power Query, or comparable platforms; communicate trends, risks, and improvement opportunities.
• Support releases and change activities, maintain operational documentation and runbooks, and identify opportunities to improve monitoring, observability, automation, operational reliability, and SLA performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level