Top Data & Analytics Jobs in Pensacola, FL

Lead development and continuous improvement of EHS safety management systems and DriveSafe program. Oversee driver scorecards, performance analytics, dashboards, and ad hoc reporting. Partner with EHS, operations, IT, and leadership to align systems, ensure data governance, drive projects, implement EHS technologies, train users, support compliance, and use data-driven insights to reduce incidents and improve safety outcomes.

Own fraud detection and mitigation for ACH payments: design controls, run investigations, analyze performance (precision/recall, financial impact), and partner with Product, Data Science, Risk ML, and Engineering to operationalize risk strategies and transition to model-driven controls.

As a Healthcare Analyst II, you will analyze healthcare data to optimize strategies, conduct quantitative analysis, and provide insights for clinical interventions, partnering with cross-functional teams.

The Analyst II will analyze data to optimize fraud strategies, develop machine learning models, and collaborate with teams to enhance product safety.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

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

Lead company-wide data governance and standards, enforce data contracts and schema/version control, manage PII/RBAC and master data, establish data-quality metrics and monitoring, grow and run the governance team, remain hands-on with data profiling and SQL, and use AI to accelerate governance work and modeling.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.