Top Analysis Reporting Jobs in Tulsa, OK

The Credit Analyst II role involves data analysis and MIS reporting for credit risk, focusing on accurate reporting and process improvement.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

As an Analytics Engineer, you'll lead the transformation layer of data, focusing on data quality, refactoring for clarity, and optimizing costs in BigQuery. You'll work closely with cross-functional teams to ensure effective data use and architecture as the foundation for AI initiatives.

The Staff Risk Analytics role involves overseeing fraud risk management, developing strategies, leading cross-functional initiatives, and providing real-time analytics in fintech.

The Data Architect will design and implement a robust data warehouse and reporting platform on Azure, ensuring data quality and governance while modernizing the existing systems.

The Solutions Architect oversees project architecture and delivery, acts as a product liaison, and contributes to the professional services development for Trimble's Construction One platform.

The Director of Statistics leads statistical initiatives in phase 3b/4 and RWE studies, provides expertise in HTA and regulatory compliance, and collaborates with cross-functional teams. Responsibilities include statistical analysis plans, Bayesian methodologies, and mentoring junior staff.

The Data and Analytics Consultant will design, develop, and implement data reporting, visualizations, and analytics solutions for clients while assisting them in data understanding and value extraction.

Trace3 seeks enthusiastic individuals for its Data Intelligence Team. The role focuses on innovative technology solutions and consulting services, fostering a collaborative and dynamic work environment.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.