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Data Science Jobs in Naples, FL (NOW HIRING)

Hertz

Sr Data Scientist - Commercial

Estero, FL

$105K/yr

Master's degree in operations research, statistics, computer science, or a related quantitative field required. * 2-5 years of industry experience in modeling, data science or operations research ...

Cliftonlarsonallen

Lead ML Ops Engineer

Naples, FL

$96K - $127K/yr

Degree in computer science, data science, or related field preferred. Technical Competencies * Advanced proficiency in Python and architectural mastery of objectoriented design across dynamically ...

Hertz

Sr Product Data Analyst

Estero, FL

$105K/yr

Description At Hertz, our senior product data analysts are responsible for developing and defining ... A bachelor's degree or higher in Computer Science, or other quantitative discipline such as ...

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$35.3K

$115.6K

$185.1K

How much do data science jobs pay per year?

As of Jul 27, 2026, the average yearly pay for data science in Naples, FL is $115,598.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,800.00 and $128,100.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Naples, FL? The most popular types of Data Science jobs in Naples, FL are:
What are popular job titles related to Data Science jobs in Naples, FL? For Data Science jobs in Naples, FL, the most frequently searched job titles are:
What cities near Naples, FL are hiring for Data Science jobs? Cities near Naples, FL with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Naples, FL as of July 2026, with employment types broken down into 3% Internship, 94% Full Time, and 3% Contract. Highlights an 90% In-person, 3% Hybrid, and 7% Remote job distribution, with an average salary of $115,598 per year, or $55.6 per hour.
Manager of Data Science

Manager of Data Science

Cliftonlarsonallen

Naples, FL

Full-time

Medical, Dental, Vision, Retirement

Posted 6 days ago

CliftonLarsonAllen rating

7.3

Company rating: 7.3 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

20th of 22 rated bookkeepers and accountants

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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About CliftonLarsonAllen

Sourced by ZipRecruiter

CliftonLarsonAllen (CLA) is a leading professional services company based in Minneapolis, MN, US. CLA operates in the accounting industry and offers a broad range of products and services such as wealth advisory, outsourcing, audit, tax, and consulting services. The company was founded in 1953 with a merger between two firms, Clifton Gunderson and LarsonAllen, in 2012. Working in accordance with their mission to create opportunities for clients, people, and communities, they have established a presence across the US, serving privately held businesses, non-profits, and governmental entities. Recognized for their contributions, CLA has received accolades such as the Innovative Firm of the Year award.

Industry

Accounting services

Company size

5,001 - 10,000 Employees

Headquarters location

Minneapolis, MN, US

Year founded

2012

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