Top Remote Data Science Jobs in Tampa, FL

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.

Analyze large marketing datasets, build predictive models for segmentation, pricing, and demand forecasting, support targeted campaigns and retention, partner with product and marketing, apply statistical and ML methods, ensure data quality with engineering, and communicate insights to stakeholders to drive conversion and retention improvements.

Senior individual contributor owning complex end-to-end ML problems for supply chain and consumer applications. Build and deploy predictive models (demand forecasting, delivery ETA, recommendations), embed with engineering teams, define MLOps standards, and advise leadership on data science strategy and investments.

This role involves analyzing EHR and insurance claims data to define clinical outcomes, developing AI models, and collaborating with technical experts for manuscript preparation.

The Data Scientist at GenLogs will build machine-learning systems, analyze large datasets, and collaborate with engineering and product teams to deliver advanced logistics intelligence solutions.

As a Data Scientist, you will analyze blockchain data to derive insights, develop and deploy predictive models, and improve product offerings.

As a Staff Data Scientist, you'll design and optimize ML systems for claims handling automation, collaborating with product and engineering teams.

As the Staff Data Scientist, you will lead the data science function, driving strategy, mentoring peers, and shaping product direction through advanced analytics and experimentation.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

Partner with Marketing as the embedded data science lead to build marketing measurement, attribution, LTV/ROAS/CAC models, run experiments, analyze the full funnel, create forecasts and dashboards, and influence channel strategy and budget allocation.

Lead cross-functional teams to identify and implement revenue-driving strategies. Own revenue optimization, develop quantitative analyses (A/B testing, causal impact), improve data pipelines and tracking, embed AI into workflows, and present insights to leadership to scale and recover revenue.

Seeking a Senior Data Scientist to lead predictive analytics and machine learning initiatives. Responsibilities include building ML models, data management, and mentoring junior data scientists. Must have expertise in AWS and strong statistical knowledge.

Lead end-to-end AI/ML initiatives to improve student retention, engagement, and enrollment. Architect and operate data pipelines, feature stores, and production ML systems; deploy, monitor, and automate models; run experimentation programing and measure business outcomes. Mentor team members and set technical standards across Product, Engineering, and CX.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

Senior data analyst/programmer using SAS or R to analyze commercial claims and EHR real-world data. Create longitudinal cohorts, derive baseline/outcome variables, assess data quality, apply epidemiologic study designs and statistical methods (regression, survival), review protocols/SAPs, and program TFLs. Familiarity with OMOP CDM and OHDSI tools is a plus; prior pharmaceutical experience preferred.

Lead data strategy and analytics for cognitive assessment studies: design algorithms and models, implement CDISC-compliant data transfers (SDTM/ADaM), produce statistical analysis plans and scientific reports, build and maintain analytics pipelines, dashboards, and visualizations, ensure data quality and QC, and present results to sponsors while managing multiple projects independently.

Embed in a core business area to define the right problems, design metrics, run analyses and experiments, build reports, surface insights, and drive data-informed decisions end-to-end to improve product, growth, AI/automation, or partnerships.

Embed within a core business area to define problems, build metrics and analyses, run experiments, generate insights from data, and drive decisions end-to-end to improve product, growth, AI/automation, or partnerships.

The Senior Data Scientist will develop machine learning systems for fraud prevention using behavioral data, collaborate across teams, and mentor junior scientists.

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.

The Senior Data Scientist will develop scalable ML models, analyze large datasets for insights, and collaborate with teams to enhance business performance through data-driven solutions.

Design, develop, and deploy causal inference and predictive models (uplift, synthetic control, DML) for customer loyalty, churn, and LTV. Build foundational data models and scalable features, perform large-scale SQL ETL, operationalize models in cloud, partner with stakeholders, and present insights to drive revenue and loyalty program optimization.

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

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.