Top Information Technology Data & Analytics Jobs in Chicago, IL

The Technical Analyst will manage performance of in-flight connectivity systems, analyze data for trends, and coordinate with teams to enhance maintenance practices and reliability metrics.

The eDiscovery Data Specialist will execute data operations, develop Python scripts, manage client communications, and optimize workflows using advanced Excel and ticketing systems.

As a Senior Business Intelligence Engineer, you will design and maintain reporting solutions, architect ETL pipelines, and implement AI use cases while collaborating with stakeholders across various business units.

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

Design, build, and maintain scalable BI solutions and Power BI dashboards for CRM performance and lifecycle analytics. Integrate AEP, RTCDP, and CRM data, ensure data quality and governance, automate reporting across brands/markets, support attribution and migration to cloud, and collaborate with cross-functional teams to deliver actionable marketing insights.

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

As a Senior Data Analyst at Bestow, you will automate data transformation pipelines, create data visualizations, ensure data quality, and collaborate with teams to drive insights in the insurance domain.

The SI Business Analyst will drive integration between business needs and technical delivery, focusing on insurance and healthcare systems. Responsibilities include capturing requirements, performing gap analysis, designing workflows, and leading cross-functional teams to optimize system performance and support digital transformation initiatives.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.