Top Analysis Reporting Jobs in Wichita, KS

The Business Analyst develops and manages reporting capabilities, builds Power BI dashboards, analyzes data trends, supports operational goals, and maintains reporting governance across various departments.

The Business Process Analyst manages reporting operations, facilitates change management, supports incident resolution, and implements process improvements to enhance reporting quality and stakeholder satisfaction.

The Impact Tracking Senior Specialist will design and implement impact measurement systems, engage stakeholders, analyze data, produce reports, and build internal capacity to demonstrate the real-world impact of Sand's programs.

The Data Engineering Lead is responsible for architecting scalable data systems, integrating ML models, and leading a technical team while optimizing performance and costs.

The CX Data & WFM Specialist will analyze CS metrics, produce reports, manage dashboards, forecast workforce needs, and liaise with finance regarding workforce costs.

The HEDIS Business Analyst IV leads data analysis to improve healthcare quality and HEDIS processes, identifies trends and risks, and collaborates across departments to enhance operational performance.

The Senior Director Analyst will provide insights for CIOs in financial services, focusing on risk strategy, technology trends, and best practices.

The Director Analyst will oversee the procure to pay lifecycle, master data management, and procurement data analytics, ensuring integrity and optimizing operations.

The Principal Data Architect will design and implement complex cloud-based data solutions, oversee data standards, and guide technical teams while maintaining client roadmaps.

The Senior Data Architect will own architectural direction for large data platforms, ensuring scalability and security while leading modernization efforts and communicating with stakeholders.

The Fraud Intelligence Analyst investigates fraud cases, translates insights for product development, identifies fraud patterns, supports revenue workflows, and builds domain expertise through high-volume casework.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.