Top Analysis Reporting Jobs in Pensacola, FL

Own end-to-end analytical lifecycle to develop and optimize business, risk, and growth strategies. Monitor portfolio and macro trends, build and interpret ML-driven models, lead cross-functional launches, mentor junior analysts, and build AI-assisted workflows to improve decisioning and measurement across products and geographies.

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

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.

The Senior Consumer Insights Analyst leads consumer insights within cross-functional teams by managing research processes, synthesizing data, and delivering actionable findings to influence product development and strategy.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

Support Finance and Sales by reconciling and validating revenue KPIs (ACV, ARR, renewals), building reporting datasets and dashboards, collaborating with CRM and data engineering teams, and participating in month-end and quarter-end close activities. Provide ad-hoc analysis and stakeholder-facing explanations of metric derivation and data quality.

Serve as a Senior Data Analytics Consultant specializing in Dynatrace and observability to analyze digital experience data, produce dashboards and reports, advise 4–8 enterprise clients, present findings to technical and executive audiences, configure tooling, influence product roadmap, and support client enablement and account growth.

Senior analytics leader who defines analytic strategy, leads a team of SQL analysts and BI developers, architects scalable frameworks for medical economics, risk, population health and value-based care, ensures methodological rigor in DBT/Spark and Quicksight dashboards, drives automation and AI integration, presents to executive stakeholders, and mentors senior analytic talent.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Lead and architect high-value healthcare analytics engagements, build reusable analytic frameworks (DBT), partner with product and engineering, mentor analysts, ensure analytic quality, and represent Arcadia externally to drive population health and value-based care outcomes.

Build and maintain production-grade data models and pipelines for the Compliance Data Mart, implement data quality frameworks and monitoring, partner with engineering to resolve data gaps, support regulatory exams and audits, and automate manual workflows into scalable pipelines and self-serve tooling.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

Partner with Sales, RevOps, Finance, and Data Engineering to convert CRM and pipeline data into actionable insights. Build and maintain pipeline and forecasting reports, dashboards, and metrics; identify risks and opportunities; improve data quality and reporting reliability; triage analytics requests; and embed AI tooling into analytics workflows to accelerate output and ensure analytical rigor.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

Lead design and governance of enterprise-scale data architecture (warehouses, lakehouses, streaming). Define standards for data quality, lineage, observability, and AI-enabled workflows. Mentor engineers, serve as technical escalation, and translate business needs into long-term data architecture and governance strategies.