Top Remote Analysis Reporting Jobs in Tulsa, OK

Build and maintain reliable data pipelines, Airflow DAGs, and Snowflake-based Data Vault/warehouse models. Implement CI/CD, automated testing, observability, and production support while partnering with stakeholders and developing insurance domain expertise.

Design, build, and operate end-to-end data pipelines and curated compliance datasets powering transaction monitoring, KYC/EDD, and screening. Ensure data quality, lineage, and audit readiness; partner with Compliance and Engineering to improve detection signal quality, define metrics, and deliver repeatable reporting and measurement frameworks for control effectiveness.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

The Lead Data Analyst will define KPIs, analyze data trends, build dashboards, and support new product launches, requiring strong SQL and Python skills.

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

As a Data Operations Analyst, you will maintain and enhance Charge Integrity SaaS by utilizing SQL and data analysis to solve complex revenue cycle problems and ensure accurate charge capture.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.