Top Analytics Jobs in Jacksonville, FL

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

Hands-on technical lead designing and delivering scalable, secure Azure-based BI and analytics solutions. Own end-to-end Power BI architecture, mentor engineers, guide implementations, optimize performance, and advise clients on governance, deployment, and AI-augmented analytics. Drive discovery, backlog priorities, cross-team alignment, reusable assets, and consulting pursuits.

Own growth and player behavior analytics across sportsbook, casino, and poker. Partner with Revenue Ops, Marketing, Product, and VIP to run retention, bonus optimization, segmentation, A/B testing, and predictive modeling using SQL, Snowflake, ML/AI tooling, and Python. Turn analysis into actionable recommendations and measurement frameworks.

Bridge enterprise customers' legacy BI to Hightouch by reverse-engineering complex marketing reports, building reusable reporting frameworks, engineering and documenting semantic/context layers, ensuring accurate SQL generation, and training non-technical marketers while collaborating cross-functionally to deliver reliable, idempotent AI-driven analytics.

Build and maintain auditable data pipelines in Snowflake and dbt to ensure financial reconciliation and audit readiness. Partner with Accounting, Operations, Engineering, and Reporting to investigate data issues, improve integrations via APIs, and own claim reimbursement and contract sales data workflows.

Lead marketing measurement initiatives (MMM, attribution, incrementality) using causal inference and validation techniques. Partner with marketing, data engineering, and vendors to deliver actionable insights, KPI frameworks, and strategic recommendations that optimize marketing ROI.

Lead Databricks-based enterprise data and analytics modernization programs. Define future-state architecture, drive platform modernization, ensure security, scalability, cost optimization, and mentor teams while delivering AI-ready data platforms and governance.

Lead end-to-end analytics for data transformation programs: scope data requirements, build scalable workflows and BI layers, perform statistical analysis, and present insights to senior stakeholders. Manage delivery, map and optimize processes, support system changes, and train business users to drive measurable efficiency and cost improvements.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Own and evolve the analytics engineering platform: design and maintain certified dbt models, enforce modeling/testing/documentation standards, build semantic and metadata layers, optimize Snowflake performance, partner with analysts and data engineering to migrate business logic and ensure reliable, AI-ready analytics, and mentor teammates on analytics engineering best practices.

Perform default reporting and analytics for mortgage servicing portfolios, validate and troubleshoot data and exception reports, conduct root-cause analysis, produce ad-hoc reports, document processes, and collaborate with default management to ensure regulatory-compliant, accurate reporting delivery.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.

Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.

Design, build, and maintain scalable, documented data models and the Gold data layer using dbt/Coalesce. Ensure data quality through automated tests, observability, version control, and CI/CD. Optimize SQL and warehouse performance, collaborate with Data Engineering and Analytics, and support semantic layers and BI catalogs to enable trusted, self-service insights for Product, Finance, and GTM teams.

Implement and manage Adobe Analytics across web and mobile, define custom tracking, collaborate with dev and stakeholders, create reports and dashboards, support A/B testing and optimization, deliver insights and training to improve digital performance.

Lead Adobe Analytics architecture and MarTech ecosystem design, implement data layers and tagging across web and mobile, ensure QA and privacy compliance, enable reporting and audience activation, and drive cross-functional measurement and governance for personalization and optimization.

Design and implement a scalable Elasticsearch-based analytics platform integrated with an Oracle data warehouse. Architect data models, ingestion/CDC pipelines, index/shard strategies, and monitoring. Optimize cluster, queries, and caching for sub-second dashboard performance, perform load testing and capacity planning, and produce operational documentation and SLAs.

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

The Enterprise Performance Analytics Engineer builds and maintains data pipelines and models, ensuring data quality and efficient reporting for analytics teams.

Lead and grow an analytics engineering team to build a trusted semantic metrics layer, scalable dimensional models, and governance. Partner cross-functionally to deliver reliable data products, improve pipelines and observability, set technical standards, and enable self-service analytics, experimentation, and ML while balancing scalability and business impact.

As an Analytics Engineer at Axios, you'll design and maintain data products and visualizations, improving decision-making through actionable insights.