Top Senior Data & Analytics Jobs in Pensacola, FL

Lead and manage the strategy, development, and operation of BECU's Enterprise Data Platform, ensuring secure and scalable data capabilities while fostering team collaboration and data governance.

The role involves developing and managing complex data sets, creating dashboards, and analyzing data for operational efficiency in healthcare. Collaboration with clinical and IT teams is essential to optimize patient outcomes and processes.

Manage underwriting analytics, collaborate with cross-functional teams, drive operational improvements, and enhance training for underwriters.

The Manager, Monitoring Coverage & Analytics leads assessments of transaction monitoring effectiveness, partners with analytics and operations teams, and supports regulatory readiness. Responsibilities include optimizing monitoring rules, analyzing metrics, and documenting findings for compliance.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

The Global Head of Pricing will lead pricing functions, optimize margins, develop pricing models, and ensure accurate billing while partnering with multiple teams.

The Senior Data Engineer will design and maintain data infrastructures, support analytics, and collaborate with stakeholders to improve data quality and governance while utilizing DBT and AWS tools.

The Senior Analyst will drive marketing strategies and performance optimization through advanced analytics, insights generation, and cross-functional partnerships, while mentoring junior team members.

The Senior Data Scientist will lead innovative data science efforts, leveraging advanced analytics, visualization, and insights from complex datasets to boost productivity.

The Sr. Data Engineer will build and maintain data pipelines, develop ETL processes, and optimize data infrastructure, collaborating across teams to ensure data reliability and performance.