Top Analysis Reporting Jobs in Tulsa, OK

Design, build, and maintain scalable data pipelines and models; collaborate with analysts and data scientists to provision prepared datasets; implement data quality, governance and monitoring; recommend technologies; lead root-cause analysis, code reviews and testing; mentor teammates and support production data environments.

The analyst will perform advanced credit risk analysis, monitor performances, provide guidance on data analysis, and ensure compliance with regulations.

The Senior Analyst of People Analytics will manage Visier platform, support data pipelines, validate data accuracy, and develop self-service dashboards ensuring analytical integrity across employee lifecycle processes.

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.

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.