Top Data Science Jobs in Jacksonville, FL

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, demand forecasting, targeting, and personalization. Collaborate with engineers, product, and stakeholders to set architecture, metrics, and production best practices; mentor data scientists; lead experimentation and deploy/monitor models using cloud and MLOps 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.

Build and deploy statistical and machine learning models for the Toast platform. Collaborate with product, engineering, and business teams to identify opportunities, develop data-driven solutions, evaluate models, and communicate insights to stakeholders. Work in a fast-paced environment and contribute to production ML systems and experimentation.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

Lead analytics and AI/ML initiatives for Financial Crime Risk Management. Work with large complex datasets to build ML and LLM-driven solutions, support regulatory and audit requests, perform ad hoc analysis, validate and document results, and communicate insights to stakeholders across the enterprise.

Develop and monitor financial crime risk models using data wrangling, statistical inference, visualization, and advanced analytics. Build production-grade models (tree-based and neural networks) in cloud environments, translate business problems to data solutions, and collaborate with engineers and stakeholders to deliver scalable transaction monitoring and AML analytics.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Embedded within a business unit, own end-to-end analytics: define problems, build metrics, run analyses and experiments, produce reports, and drive recommendations to product, growth, and partnerships using SQL/Python. Communicate findings to stakeholders and ensure data-driven decision-making and measurable outcomes.

Embedded Data Scientist responsible for defining problems, building metrics, analyses, experiments and reports, and driving data-informed recommendations and outcomes across growth, product, AI/automation, and partnerships. You'll execute end-to-end, influence stakeholders, and deliver measurable impact using SQL, Python, Metabase, and Jupyter Hub.

The Sr. Football Data Scientist will build, deploy, and refine analytical models for football insights, managing large datasets and collaborating with teams for high-quality analytics solutions.

Develop and operationalize graph-based analytics for fraud detection and investigative analysis. Build graph models, apply graph algorithms and ML to detect anomalies, support entity resolution, create visualizations and dashboards, and collaborate with investigators and stakeholders to deploy and maintain production solutions.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Lead end-to-end data science for a priority vertical (Insurance), building, validating, and deploying ML models that drive ROAS and lead quality. Partner with stakeholders and ML engineering to monitor live performance, iterate models, and identify new modeling opportunities to improve revenue and media efficiency.

The Data Scientist will enhance statistical models for forecasting, analyze datasets for operational planning, and communicate insights to stakeholders.

This role involves leading data science projects, designing technical solutions, implementing machine learning methodologies, and developing data workflows for cybersecurity applications.

The Data Scientist designs and builds data structures for AI applications, manages vector and feature stores, leads data discovery, and collaborates on responsible data use while ensuring high-quality, governed datasets for ML models and applications.

The Data Scientist II will develop machine learning algorithms, architect data solutions, and support cybersecurity initiatives by analyzing complex data sets.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Lead design and evolution of large-scale nodal power market models. Define mathematical approaches, develop optimization/forecasting methodologies (MILP, SCUC/SCED), collaborate with engineers to productionize models, work with product and customers to translate market problems into software, mentor data scientists, and guide long-term product strategy.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Develop and refine predictive models, perform exploratory data analysis, and generate AI-driven insights for DoD missions. Integrate multi-source data, apply geospatial analytics, iterate models via Agile sprints, produce performance and cost reports, and optimize analytic workflows for operational deployment.