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Data Science Developer Jobs in Florida (NOW HIRING)

INFOTRON

Data Scientist / ML Engineer

Cape Coral, FL · Remote

$35/hr

We're looking for a Data Scientist / Developer whose work will directly contribute to health, sustainability, and wellness innovations. From building robust data pipelines to developing intelligent ...

Lorven Technologies, Inc.

Data Scientist

Tampa, FL

Work closely with commercial, supply chain, and engineering teams to build ML solutions that ... Skills / Experience: * 8+ years in data science or Applied ML roles; 3+ years of experience in ...

Lorven Technologies

Data Scientist

Tampa, FL · On-site

Work closely with commercial, supply chain, and engineering teams to build ML solutions that ... Skills / Experience: * 8+ years in data science or Applied ML roles; 3+ years of experience in ...

Lorven technologies

Data Scientist

Tampa, FL · On-site

$130K - $140K/yr

Work closely with commercial, supply chain, and engineering teams to build ML solutions that ... Skills / Experience: * 8+ years in data science or Applied ML roles; 3+ years of experience in ...

Clarity Innovations

Data Scientist

Tampa, FL · On-site

Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake.

Core One

Data Scientist

Tampa, FL · On-site

Required : • Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, Electrical Engineering, or a related technical discipline; Master's degree or PhD preferred. • Minimum ...

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$12

$42

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How much do data science developer jobs pay per hour?

As of May 31, 2026, the average hourly pay for data science developer in Florida is $42.46, according to ZipRecruiter salary data. Most workers in this role earn between $34.86 and $50.29 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Developer, and why are they important?

To thrive as a Data Science Developer, you need strong expertise in statistics, machine learning, programming (Python, R), and a background in computer science or a related quantitative field. Familiarity with data analysis tools (such as Pandas, NumPy, and scikit-learn), cloud platforms (like AWS or Azure), and experience with databases (SQL/NoSQL) are typically required, and certifications like Microsoft Certified: Azure Data Scientist Associate can be beneficial. Strong problem-solving skills, effective communication, and the ability to collaborate with cross-functional teams help you stand out. These skills are essential for building data-driven solutions that translate complex data into actionable business insights.

What are some common challenges Data Science Developers face when integrating models into production environments?

Data Science Developers often encounter challenges in bridging the gap between developing models in experimental settings and deploying them into scalable, reliable production systems. Issues such as data inconsistencies, version control, and ensuring model reproducibility can arise. Additionally, collaborating effectively with DevOps and engineering teams to automate deployment pipelines and monitor model performance is crucial for long-term success. Understanding both machine learning and software engineering best practices helps overcome these hurdles and ensures smooth, efficient integration.

What is a Data Science Developer?

A Data Science Developer is a professional who combines expertise in programming, statistics, and data analysis to build models and algorithms that extract insights from large datasets. They often work with machine learning techniques, data visualization, and various data processing tools to solve business problems. Data Science Developers collaborate with other teams to design and implement data-driven solutions, and are skilled in languages like Python, R, or Scala. Their work is essential for organizations looking to leverage data for decision-making and innovation.

What is the difference between Data Science Developer vs Data Analyst?

AspectData Science DeveloperData Analyst
Required SkillsProgramming, machine learning, data modelingData visualization, statistical analysis, reporting
CertificationsData Science certifications, Python/R expertiseExcel, SQL, Tableau certifications
Work EnvironmentTech companies, startups, R&D teamsBusiness departments, marketing, finance
Job FocusDeveloping algorithms, predictive modelsInterpreting data, generating reports

While both roles analyze data, Data Science Developers focus on building models and algorithms to solve complex problems, often requiring programming and machine learning skills. Data Analysts primarily interpret existing data sets to generate insights and reports for business decisions. The roles overlap in data handling but differ in technical depth and objectives.

What are popular job titles related to Data Science Developer jobs in Florida? For Data Science Developer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Data Science Developer jobs in Florida look for? The top searched job categories for Data Science Developer jobs in Florida are:
Data Science Developer jobs near you
Infographic showing various Data Science Developer job openings in Florida as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $88,308 per year, or $42.5 per hour.

Manager of Data Science

Clifton Larson Allen

Orlando, FL • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 11 days ago

Job description

CLA is a top 10 national professional services firm where our purpose is to create opportunities every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you.

CLA is dedicated to building a culture that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other.

CLA is looking to hire a Data Science Director to join our growing Internal IT team.

About the role:

CLA is looking to hire a Manger of Data Science

This role constructs complex solutions that integrate data wrangling, visualization, and advanced modeling techniques into a seamless workflow using software development best practices in R, Python, or other scripting languages. They are comfortable working with APIs, web scraping, and SQL/no-SQL databases. They automate business workflows while integrating stochastic/numeric algorithms in the process. This role will develop more autonomy to develop solutions and will lead others, take on administrative tasks, perform support roles, and get involved in new business development.

As Manager of Data Science, you will have to following responsibilities:

Leadership
  • Provide daytoday leadership, coaching, development, and performance management.
  • Mentor and guide analysts, supporting onboarding, skill development, and continuous learning across career stages.
  • Conduct workload planning, prioritization, and resource allocation to support multiple concurrent initiatives.
  • Build and sustain a highperforming team culture rooted in collaboration, quality, accountability, and innovation.

Technical Oversight

  • Lead and oversee large scale analytical and AI initiatives, including data acquisition, transformation, modeling, AI system development, automation, and insight generation.
  • Provide technical oversight and review of analytical approaches, models, and AI systems to ensure sound methodology, reproducibility, and scientific rigor.
  • Guide the development and application of advanced statistical, machine learning, and AI-driven solutions, including predictive models, computer vision, large language models (LLMs), and agent-based systems.
  • Lead the design and oversight of AI-enabled systems, including prompt engineering strategies, retrieval-augmented generation (RAG), embeddings, and agentic workflows.
  • Establish and evolve analytical and AI best practices, documentation standards, and technical frameworks across the team.
  • Ensure standards for model and AI system validation, monitoring, evaluation, documentation, and responsible AI use are consistently applied.
  • Partner with engineering, IT, and data platform teams to enable scalable, reliable, and well governed solutions.

Workflow Management

  • Own delivery outcomes for data science and AI workstreams, ensuring solutions meet quality, performance, and business expectations.
  • Translate business objectives into clear analytical and AI priorities, balancing near term delivery with long term capability building.
  • Oversee planning, prioritization, and resourcing across projects and teams.
  • Monitor solution performance, validation results, and model or AI system stability; guide troubleshooting of complex data, model, or AI issues.
  • Ensure solutions are productionized effectively, with clear ownership, monitoring, and integration into business workflows.
  • Establish, refine, and enforce standards for documentation, reproducibility, quality assurance, and governance.
  • Remove obstacles, manage risks, and ensure consistent execution across initiatives.

CrossFunctional Collaboration

  • Serve as a primary point of contact for business and functional leaders on analytics and AI initiatives.
  • Partner with stakeholders to define business questions, success metrics, analytical frameworks, and delivery expectations.
  • Coordinate work across teams, offices, and disciplines to ensure alignment of analytical and AI approaches and outcomes.
  • Communicate progress, risks, and results clearly to both technical and non technical audiences.
  • Evaluate and recommend adoption of new data sources, technologies, and analytical and AI tools.
  • Contribute to enterprise level analytics and AI strategy, including identifying high impact use cases and guiding their transition from concept to production.

What you will need:

8 years of relevant experience required.

  • Experience in data analytics, statistics, data science, AI, financial consulting, computer science or related field required.
  • Experience with APIs, web scraping, SQL/no-SQL databases, and cloud-based data solutions required.
  • Supervisory experience required.

Education

Bachelor's degree is required. Combination of relevant experience, education, and training may be accepted in lieu of degree.

  • Degree in Statistics, Computer Science, Economics, Analytics, Data Science (e.g., Informatics, Data Science, Health Data Science), AI, or related field preferred.
  • Masters in a Data Science/Analytics/AI is a plus

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Wellness at CLA

To support our CLA family members, we focus on their physical, financial, social, and emotional well-being and offer comprehensive benefit options that include health, dental, vision, 401k and much more.

To view a complete list of benefits click here.

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