Top Senior Data Science Jobs in Jacksonville, FL

Lead analytics initiatives to deliver strategic insights for consumer markets. Develop advanced analytics and BI solutions, manage teams, engage stakeholders, implement cloud analytics, and coach diverse teams to improve performance and decision-making.

Lead research and engineering of production-grade LLM/GenAI systems for cybersecurity: design models and architectures, drive data labeling and evaluation, collaborate with product and engineering to deploy scalable solutions, mentor data scientists, set technical strategy, and advance AI safety, red-teaming, and applied ML innovations for detection and operational use.

Lead advanced analytics and ML efforts to extract insights from large-scale historical data, design features and data representations for models and LLM/agentic systems, partner with product and engineering to build data pipelines and prototypes, evaluate AI workflows, and drive innovation through experiments and empirical analysis to inform product strategy.

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.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

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.

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.

Lead complex modeling projects combining deep learning, LLMs, and traditional techniques. Prototype, deploy, and monitor production models, mentor data scientists, collaborate with engineering/product, and translate results into business impact for insurance customers.

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.

The Senior Data Scientist partners with Customer Success to perform deep-dive analyses, diagnose metric shifts, build predictive models (churn/upsell), apply causal inference and experimentation, measure business impact, and develop AI/LLM solutions. Responsibilities include self-serving across the data stack for extraction, pipelining, and dashboards, defining KPIs, and delivering actionable insights to reduce churn, drive revenue, and improve operational efficiency.

Lead development and deployment of large-scale LLM and GenAI solutions for cybersecurity. Drive research strategy, model training, evaluation, safety/red-teaming, and cross-functional productization. Mentor data scientists, set technical standards, and represent the team through publications and thought leadership.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Build and scale production-ready generative AI applications: design multi-agent workflows, implement advanced RAG with vector DBs, integrate/swap LLMs, fine-tune models, and deploy scalable FastAPI/Docker services with monitoring and optimization for latency, cost, and reliability.

Build and scale production Generative AI applications: design multi-agent systems and LangGraph workflows, implement advanced RAG with vector DBs, integrate and fine-tune LLMs, deploy FastAPI async services in Docker, and optimize GenAI performance, cost, and monitoring.

Design, build, and deploy production-ready generative AI applications: architect multi-agent workflows, implement advanced RAG with vector DBs, integrate/swap LLMs, fine-tune models, and deliver scalable FastAPI-based services with monitoring, CI/CD, and containerized deployment.

Design, build, and deploy machine learning and generative AI models (including LLMs and text-to-image). Analyze large datasets, run A/B and statistical tests, collaborate with data engineering and engineering teams, and create dashboards/visualizations to communicate insights. Optimize data pipelines and model performance to support data-driven decisions.

Owner of analytics for EHR, revenue cycle, and operations: design and run experiments, analyze financial and operational metrics, investigate billing and account issues, and deliver actionable insights to Product, Operations, Finance, and Customer Experience to improve accuracy, reduce friction, and support growth.

Designs, analyzes, and interprets clinical trial, RWE, and observational data for a medical device. Develops statistical plans, predictive models, and ensures data quality, regulatory compliance, and traceability. Collaborates with clinical, regulatory, and data teams, supports submissions and publications, mentors interns, and represents the company externally.

Design, implement, and maintain marketing inference models (e.g., MMM and attribution). Analyze large datasets and A/B/uplift experiments with rigorous statistics, build predictive and causal models, partner with marketing to generate testable ideas, and communicate insights to drive marketing decisions.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Design, train, fine-tune, deploy, and monitor Large Language Models for government mission applications. Collaborate with cross-functional teams, ensure data preprocessing and model performance, present findings to stakeholders, and mentor junior data scientists.

As a Senior Marketing Data Scientist, you will conduct quantitative analyses, manage marketing tests, and provide actionable insights to enhance marketing performance and investment effectiveness.

Design, develop, train, evaluate, deploy, and monitor scalable AI/ML models to predict member outcomes. Perform EDA, feature engineering, data extraction with SQL/Python/R, ensure data quality and fairness, build CI/CD pipelines, containerize models (Docker/Kubernetes), and communicate results to non-technical stakeholders. Support model maintenance, logging/alerting, unit testing, and team best-practice initiatives.

Lead product experimentation and ML initiatives: design and run A/B tests and causal analyses, build and deploy ML models (GBMs, random forest, logistic regression) using Python and MLflow, partner with Product/Design/Engineering, translate results into executive-facing recommendations, and establish experimentation and ML best practices.