Top Senior Analysis Reporting Jobs in Houston, TX

The role involves leading data analytics to drive strategy, conduct risk assessments, and improve data systems within the data strategy team.

Lead initiatives in data architecture and analytics, utilizing Qlikview and Tableau to optimize decision-making and drive insights. Mentor team members while adhering to data governance standards.

The Sr Manager of Payor Performance Analytics drives financial, analytical, and operational components of payer contracting, overseeing reimbursement modeling and ensuring successful contract negotiations and implementation.

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

The Supply Chain Analytics Manager gathers and analyzes data to drive insights, creates dashboards, and establishes data practices for informed decision-making.

Lead RPA (Risk, Performance, and Attribution) data domain, ensuring data integrity, managing product roadmaps, applying data modeling techniques, and driving data governance.

Lead advanced analytics for work management systems, build dashboards and models, perform root-cause and data quality analysis, translate business requirements into scalable solutions, collaborate with IT and stakeholders, mentor analysts, and contribute to data governance and analytics modernization.

As a SAS Statistician, you will analyze Medicare claims data to drive insights for pharmaceutical companies, standardize processes, and train team members in SAS.

Lead analytics and BI efforts to drive operational performance: build and maintain dashboards and ETL pipelines, analyze KPIs and drilling performance, support performance-improvement initiatives, collaborate with data scientists and BI/devops, and manage daily operational reporting and optimization tools.

Design and own end-to-end data domains and pipelines for plant sensors, lab results, and historians. Build schemas, ensure data quality, observability, and lineage, and supply model-ready time-series and analytical datasets to ML and operations teams. Mentor junior engineers and define data contracts.