Senior Data Science Engineer Jobs in Florida
Senior Data Science Engineer jobs in Florida are in active demand, concentrated in financial services, healthcare technology, defense contracting, and logistics, with openings ranging from mid-level to principal engineer. Miami, Tampa, and Orlando generate the most consistent hiring, anchored by employers such as Citrix, Lockheed Martin, and AdventHealth that maintain large technical workforces across the state. The most sought-after specialties in Florida listings include machine learning platform engineering, real-time analytics for healthcare systems, and MLOps infrastructure. Find a role that fits below and apply directly.
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The analyst will work with structured and unstructured data, build and maintain the reporting layer, develop forecasting and predictive models, validate those models against actual results, and automate manual processes. The standard for this role is defensibility: every number produced must reconcile to its source system, and every model must be documented, tested against data it was not trained on, and explainable to a non-technical audience. Selecting the simplest method that answers the question is preferred over sophistication for its own sake.
This position supports the executive team crossing all departments of the Company. Initial priorities will center on sales reporting, expanding to enterprise analytics as the reporting foundation matures.
- Collect, clean, validate, and transform data from multiple source systems, including project management, accounting, CRM, and field data collection platforms.
- Develop dashboards, reports, and visualizations that provide actionable insights.
- Analyze historical trends, operational performance, productivity metrics, and business outcomes, including job-level margin, estimate versus actual variance, backlog and pipeline conversion, win rates by client and business unit, and receivable aging and collection cycle time.
- Create recurring and ad hoc reporting for leadership teams.
- Identify patterns, risks, and opportunities through quantitative analysis.
- Build and maintain the queries, extracts, and pipelines that feed the reporting layer, including API-based extraction from source systems.
- Reconcile reporting to the general ledger and to source systems so that analytical output and financial reporting do not diverge.
- Build forecasting models for revenue, backlog conversion, labor and equipment demand, and cash flow, accounting for the seasonality and catastrophe-driven volatility inherent to storm restoration work.
- Design and interpret experiments, quantify statistical significance, and measure realized business impact against forecast.
- Present quantitative findings with stated confidence, known limitations, and the reasoning behind method selection.
- Apply large language model tooling to production analytical workflows, including structured data extraction from unstructured documents, classification, and summarization, rather than ad hoc manual prompting alone.
- Develop AI-assisted processes to streamline reporting, research, document review, and decision support, with human review controls at each output stage.
- Evaluate emerging AI capabilities and recommend practical business applications, including build versus buy assessment and cost per unit of output.
- Build automated workflows that reduce manual effort and increase efficiency
- Ensure data accuracy, integrity, and consistency across reporting systems.
- Support data governance initiatives, validation processes, and data quality improvements.
- Partner with stakeholders to establish reporting standards and best practices.
- Document data sources, transformations, model logic, and code so that all work is reproducible by someone other than the author.
- Partner with business leaders to understand strategic priorities and deliver data-driven recommendations.
- Present findings to both technical and non-technical audiences.
- Support initiatives across Sales, Operations, Finance, Marketing, and Executive Leadership.
- Translate complex analyses into actionable business recommendations.
- Challenge analytically unsupported conclusions, including those already held by leadership, and state plainly where available data is insufficient to answer the question asked.
- 5 years of progressive experience in data analytics, data science, business intelligence, or a related quantitative field, including hands-on ownership of both reporting and predictive modeling work.
- Strong analytical and problem-solving skills with experience interpreting large datasets.
- SQL proficiency sufficient to write and optimize multi-table joins, aggregations, and window functions against a production database without assistance.
- Working proficiency in Python or R for data manipulation, statistical analysis, and modeling (for example pandas, scikit-learn, stats models, or equivalent libraries).
- Demonstrated experience building, validating, and putting into use at least one forecasting or predictive model that informed an operating decision.
- Expert proficiency in Excel, including advanced formulas, pivot tables, dynamic financial and operational models, and AI‑assisted model development.
- Proficiency in CRM platforms, with hands‑on experience across multiple systems; ability to navigate, maintain data integrity, and extract insights across different systems environments.
- Proficiency in Power BI, including dashboard design, DAX formulas, and data modeling.
- Working proficiency with current AI tooling applied to real analytical work, including prompt design, structured output, and validation of AI-generated results before use.
- Excellent communication skills with the ability to translate data into clear insights.
- Background in construction, restoration, insurance, or another project-based industry is not required but is a plus.
- Experience building automated dashboards and reporting systems.
- Demonstrated ability to use AI for prospect and client research, including synthesizing information from multiple sources into actionable sales intelligence and executive‑ready presentations.
- Experience with cloud data platforms and pipeline orchestration
- Experience with large language model APIs, retrieval methods, embeddings, and evaluation techniques.
- Bachelor's degree in statistics, mathematics, economics, data science, computer science, engineering, business analytics, or another quantitative discipline.
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Where Florida roles are concentrated, by current openings.
Senior Data Science Engineer Job Market in Florida
A snapshot from current Florida openings, updated as new roles post.
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What Florida Employers Look For
The qualifications that appear most often in senior data science engineer jobs across Florida.
- Bachelor's or master's degree in computer science, statistics, or a closely related field
- Five or more years of hands-on experience in data science and machine learning engineering
- Proficiency in Python, Spark, and cloud platforms such as AWS, Azure, or Google Cloud
- Experience designing and deploying end-to-end ML pipelines in production environments
- Strong knowledge of MLOps practices including model monitoring, versioning, and CI/CD integration
- Demonstrated experience collaborating with cross-functional teams on data-driven product decisions
Senior Data Science Engineer Jobs in Florida: Frequently Asked Questions
How do you become a senior data science engineer in Florida?
The most direct path is a bachelor's or master's degree in computer science, data science, statistics, or a related technical field, followed by several years of progressive engineering experience. Florida does not require a state-issued license for this role. Large employers across Miami's fintech corridor, Tampa's health-tech sector, and Orlando's defense and simulation industry generally require a strong portfolio of production ML work and, increasingly, cloud certifications from AWS or Google Cloud.
How much do senior data science engineers make in Florida?
Senior data science engineers in Florida earn a median of about $115,820 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $63,080 for the lowest 10% to over $174,140 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior data science engineers in Florida?
Employers hiring senior data science engineers in Florida right now include Moffitt Cancer Center, University of South Florida, and blueteam, based on current listings on Migrate Mate as of August 2026. Florida's mix of financial services headquarters in Miami, defense contractors near Orlando, and large health systems like AdventHealth and Tampa General Hospital creates a diverse and consistent employer base for this role.
Which Florida cities have the most senior data science engineer jobs?
Tampa, Miami, and Doral have the most senior data science engineer openings in Florida. Miami's concentration of fintech and financial analytics firms drives the bulk of those listings, while Tampa's health-technology and insurance sectors and Orlando's defense and simulation industry account for strong and steady demand outside the southeastern corridor.
Are there remote senior data science engineer jobs in Florida?
Yes, and more than most fields. Senior data science engineering is a desk-based, tool-heavy role that translates well to remote work. About 0% of senior data science engineer openings tied to Florida are remote or hybrid as of August 2026, reflecting how widely Florida-based employers have adopted distributed technical teams. Model development, pipeline engineering, and research work are the functions most commonly offered fully remote.
How can I get hired as a senior data science engineer in Florida with little or no experience?
The most realistic entry point is a data analyst or junior data scientist role at a Florida employer, then building toward engineering responsibilities over time. AdventHealth, Lockheed Martin, and several Miami-based fintech firms run structured associate or rotational programs for recent graduates. A portfolio of end-to-end projects hosted publicly, combined with a cloud certification, gives candidates a measurable edge. Adjacent roles such as data analyst, business intelligence developer, or machine learning research assistant are common stepping-stone positions at Florida employers.
Where can I find and apply to senior data science engineer jobs in Florida?
You can find and apply to senior data science engineer jobs in Florida on Migrate Mate, which lists current Florida openings updated regularly. Find roles that fit your experience and location and apply directly through each listing.
See All 11 Senior Data Science Engineer Jobs in Florida
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