Top Analysis Reporting Jobs in Tulsa, OK

Lead design and implementation of the commercial data and systems foundation for launch and growth. Own Salesforce-led commercial systems, integrations, data warehouse, MDM, analytics enablement, governance, and scalable delivery to support commercial operations, reporting, and compliance.

Design, build, and own data infrastructure and ETL/ELT pipelines (Airflow, S3, Lambda) into a governed Snowflake warehouse. Implement data quality, IaC (Terraform/CDK), CI/CD, and analytics solutions (SQL, Tableau). Enable ML/LLM use cases like forecasting and anomaly detection and deliver automated reporting and data-driven marketing outputs.

Lead market and client-level fundraising data analysis and publish original research and benchmarks. Partner with Sales, Customer Success, and Marketing to produce ROI cases, client insights, and thought leadership. Present findings publicly at conferences, build repeatable insight frameworks and tools, and translate data into persuasive narratives for advancement leaders.

As a Quantitative Researcher, apply economic and statistical models to large-scale data, collaborating to solve quantitative challenges across industries.

Lead a team of analysts in Fraud & Safety operations, defining KPIs, designing experiments, optimizing performance, and enabling data-driven decisions globally.

As a Data Engineer, you will build and maintain data ingestion pipelines, develop data transformations, and migrate SQL Server processes to Azure-native solutions, supporting marketing campaigns and analytics teams.

The Senior Data Analyst will lead data analysis and reporting in experiential marketing, working with stakeholders to translate data into insights and improve business decisions. Key tasks include building data pipelines, ensuring data quality, and creating dashboards for visualization of key metrics.

Build and maintain scalable ETL pipelines using Python, Spark, and Airflow; collaborate with AI/ML and Product teams to deliver AI-native data products; identify and resolve ETL bottlenecks; ensure code quality through reviews and tests; own sprint deliverables and contribute to roadmap planning and major epics.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

Use statistical modeling, data analysis, and visualization to generate actionable insights that improve loan origination and production. Collaborate cross-functionally to design, test, and implement data-driven strategies, maintain data integrity, and communicate results to stakeholders to influence business decisions.