Top Data & Analytics Jobs in Jacksonville, FL

Lead day-to-day management of multi-year data projects (Neighborhood Vitality Index, Hope Starts Here). Conduct quantitative and qualitative analysis, design and analyze surveys, coordinate with external partners and internal teams, perform stakeholder outreach and engagement, and produce accessible data products and communications for non-technical audiences to inform decision-making across Detroit-area organizations.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.

Lead development and scaling of financial analytics: build data models, dashboards, and reporting; translate financial data into executive insights; embed predictive analytics; partner with Finance, IT, and business units to improve data quality, governance, forecasting, and automation.

The Data Product Manager defines the reporting roadmap, manages KPI alignment, collaborates cross-functionally, ensures data quality, and leads continuous improvement in analytics processes.

The Workday Reporting & Data Analyst will design and optimize reporting solutions, enhance data accuracy, and deliver insights through Workday and Power BI while collaborating with HR leaders.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.

As a Senior Data Engineer, you will design and optimize data pipelines, enhance system efficiency, and collaborate with teams to drive health outcomes using large healthcare datasets.

Own and implement the canonical data model and governance for a multi-tenant MEP SaaS platform. Architect data for AI/ML readiness (RAG, embeddings, vector search), design polyglot persistence and lake/lakehouse pipelines, lead staged modernization and migrations, produce hands-on prototypes and in-repo guardrails, and partner with platform, DB engineering, and ML teams to ensure data quality, lineage, and observability.

Build and maintain scalable Python-based data pipelines and backend services for analytics and ML workflows. Design software systems, support analytics/model training and deployment platforms, implement CI/CD and IaC, manage AWS/on-prem environments, monitor and improve pipeline reliability, and evaluate new AI technologies to increase platform efficiency.