Top Remote Data Science Jobs in Pensacola, FL

Design and evaluate predictive and generative models, extract insights from disparate clinical and product data, build and partner on data pipelines, run rigorous evaluations and experiments, and deliver time-sensitive ad hoc analyses to product, engineering, and clinical stakeholders.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Hands-on senior data scientist splitting work between SQL Server data engineering (ETL, pipeline modernization, data quality) and analytics delivery (Power BI semantic models, dashboards, statistical and predictive modeling). Duties include designing migration options, implementing Python-based cleansing and reproducible analytics, building ETL/deployment processes, responding to ad hoc leadership data requests, and documenting systems for stakeholders. Must obtain VA background/PIV and be a U.S. citizen.

Lead Data Scientist will support advanced analytics, predictive modeling, and machine learning initiatives for clinical decision-making in healthcare. Responsibilities include algorithm design and compliance with VA governance standards.

Design, build, and deploy ML models across diverse use cases; work with managed cloud ML platforms and containerized solutions; collaborate with engineers on production integration and MLOps best practices; preprocess and analyze large datasets; mentor teammates and influence technical direction; translate complex ML concepts for technical and non-technical stakeholders.

Lead end-to-end client ML engagements: scope problems, design, build, and deploy production ML solutions across cloud and containerized stacks. Lead and mentor small teams, manage client relationships, evaluate emerging tools, and ensure models are production-ready and explainable to technical and non-technical stakeholders.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

Design, develop, and deploy time-series and machine-learning forecasting models (ARIMA, SARIMA, ETS, XGBoost, LightGBM) for demand planning, inventory, and sales forecasting. Perform large-scale SQL data processing, operationalize models in cloud environments (Azure preferred), present insights, and lead client workshops.

The role involves building and validating Marketing Mix Models and geo-experiments, managing measurement infrastructure, and communicating insights to stakeholders.

Design and build custom measurement products by combining Nielsen datasets; develop statistical and ML models; write production-quality SQL, Python, and PySpark; build reusable ETL pipelines; use AI tools and design agentic workflows; translate stakeholder requests, document methodology, and collaborate with Research, Sales, and Insights teams.

Design, build, validate, deploy, and monitor machine learning and generative AI solutions for healthcare and life sciences. Work with EHR, claims, and registry data to produce clinical predictions, operational optimizations, and LLM-powered applications. Translate results for stakeholders, document best practices, and mentor client teams.

As a Senior Data Scientist, you'll lead projects leveraging data to enhance healthcare outcomes, mentor team members, and align data efforts with business goals.

The Senior Data Scientist will analyze and optimize marketing funnels, build statistical models, conduct experiments, collaborate with teams, and mentor junior members.

Senior individual contributor who builds statistical models and experiments to optimize acquisition, conversion, retention, and lifetime value. Partners with Product, Marketing, and Engineering to define data requirements, analyze A/B tests, perform cohort and funnel analyses, communicate findings to stakeholders, and mentor junior team members while contributing to analytics best practices.

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

Lead end-to-end data science initiatives across pricing, dispatch, ETA, routing, and forecasting. Turn ambiguous logistics problems into production ML solutions, build data pipelines, partner with engineering to deploy models, establish evaluation and A/B testing, and work directly with customers and leadership to measure business impact.

Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.