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Data Scientist Jobs in Boca Raton, FL (NOW HIRING)

Td

Data Scientist - FCRM

Fort Lauderdale, FL · On-site

$96K - $155K/yr

The Data Scientist III provides technical leadership across the overall Analytics function which may have an enterprise mandate. This role generally provides deep technical knowledge and expertise in ...

Haystack News

Senior Data Scientist

Fort Lauderdale, FL · On-site

Join our team at Haystack News as a Senior Data Scientist and become a pivotal force in redefining user experiences through cutting-edge algorithm enhancements. In this role, you'll leverage your ...

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All JobsData Scientist JobsData Scientist Jobs in Boca Raton, FL

Data Scientist information

See Boca Raton, FL salary details

$35.5K

$116.1K

$185.9K

How much do data scientist jobs pay per year?

As of Jun 15, 2026, the average yearly pay for data scientist in Boca Raton, FL is $116,124.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,200.00 and $128,700.00 per year, depending on experience, location, and employer.

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, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks, data visualization tools, and big data platforms like TensorFlow, Tableau, and Hadoop, as well as certifications in data science, are highly valued. Excellent problem-solving skills, curiosity, and the ability to communicate complex findings clearly set outstanding data scientists apart. These skills and qualities are crucial for extracting actionable insights from data, driving business decisions, and collaborating effectively with stakeholders.

What Do Data Scientists Do?

Data scientists collect, confirm, and interpret data to determine useful information for their employer. They help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information data scientists get from the records they gather helps businesses make major decisions in critical areas, such as product development, sales and marketing techniques, and client retention. Data scientists are highly educated; the majority of them have at least a master's degrees, and many have doctorates. Data scientists are valuable members of organizations in many different industries, including pharmaceuticals, manufacturing, and banking.

Is a data scientist job still in demand?

Yes, data scientist roles remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and the field continues to grow as organizations seek to leverage big data for competitive advantage.

What are Data Scientists?

Data Scientists are professionals who use statistical, analytical, and programming skills to collect, analyze, and interpret large volumes of data. They extract insights and trends from complex data sets to help organizations make data-driven decisions. Data Scientists often work with machine learning, data mining, and big data technologies to build predictive models and solve business problems. Their work bridges the gap between technical data analysis and actionable business strategy.

What does a data scientist do exactly?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use statistical techniques, programming languages like Python or R, and tools such as SQL and machine learning algorithms to interpret data and communicate findings to stakeholders.

Is 30 too late for data science?

Data scientists can enter the field at any age, including 30 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science from different backgrounds by acquiring relevant skills such as programming, statistics, and machine learning through courses or certifications. Age is generally not a barrier if you develop a strong portfolio and stay current with industry tools and techniques.

What is the difference between Data Scientist vs Data Analyst?

AspectData Scientist
Required CredentialsDegree in Computer Science, Statistics, or related field; often requires advanced degrees
Work EnvironmentResearch and development, predictive modeling, machine learning projects
Employer & Industry UsageTech companies, finance, healthcare, consulting firms
Common Search & ComparisonOften compared due to overlapping skills in data analysis and modeling

Data Scientists focus on building predictive models, advanced analytics, and machine learning, often requiring higher-level technical skills and education. Data Analysts primarily interpret existing data, generate reports, and support decision-making with descriptive analytics. While both roles analyze data, Data Scientists handle complex modeling and predictive tasks, whereas Data Analysts focus on data interpretation and reporting.

What jobs does data science do?

Data science involves analyzing large datasets to extract insights, build predictive models, and support decision-making across various industries. Data scientists often work with programming languages like Python or R, utilize machine learning techniques, and communicate findings to stakeholders. They can be employed in fields such as finance, healthcare, marketing, and technology, often requiring strong analytical skills and knowledge of statistical methods.

What are some typical projects Data Scientists work on, and how do they collaborate with other teams?

Data Scientists often work on projects such as building predictive models, analyzing large datasets to uncover trends, and developing data-driven solutions to business problems. They regularly collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to ensure that their insights are actionable and aligned with business goals. Effective communication and teamwork are essential, as Data Scientists frequently need to present complex findings to non-technical stakeholders and incorporate feedback from various departments.
More about Data Scientist jobs
What are the most commonly searched types of Data Scientist jobs in Boca Raton, FL? The most popular types of Data Scientist jobs in Boca Raton, FL are:
What are popular job titles related to Data Scientist jobs in Boca Raton, FL? For Data Scientist jobs in Boca Raton, FL, the most frequently searched job titles are:
What job categories do people searching Data Scientist jobs in Boca Raton, FL look for? The top searched job categories for Data Scientist jobs in Boca Raton, FL are:
What cities near Boca Raton, FL are hiring for Data Scientist jobs? Cities near Boca Raton, FL with the most Data Scientist job openings:
Data Scientist jobs near you

Data Scientist

Purple Drive Technologies

Fort Lauderdale, FL • On-site

Full-time

Posted 16 hours ago

Job description

Overview:
Role Name: Data Scientist
Location: Sunrise, FL
Experience Required: 6-10 Years
Job Summary
We are seeking a highly skilled Data Scientist with strong expertise in Python, PostgreSQL, and PyTest to design, develop, and deliver advanced data-driven solutions. This role focuses on building statistical and predictive models, performing deep analytical research, and ensuring high-quality, test-driven data pipelines for enterprise-grade applications.
The ideal candidate is analytical, detail-oriented, and capable of translating complex datasets into actionable business insights while maintaining robust testing and data integrity standards.
Key Responsibilities
Data Modeling & Analytics
  • Design, build, and optimize advanced statistical and predictive data models.
  • Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
  • Apply statistical techniques and machine learning methods to solve complex business problems.
Data Engineering & Databases
  • Develop and optimize data workflows using Python.
  • Write efficient, scalable queries using PostgreSQL for large datasets.
  • Ensure data quality, consistency, and integrity across data sources.
Testing & Quality Assurance
  • Implement automated testing frameworks using PyTest for data pipelines and models.
  • Validate model outputs, transformations, and data accuracy.
  • Ensure adherence to test-driven development (TDD) and best practices.
Collaboration & Communication
  • Work closely with cross-functional teams including Data Engineers, Product Managers, and Business Analysts.
  • Translate analytical findings into clear insights, dashboards, and reports for stakeholders.
  • Document methodologies, assumptions, and model performance metrics.
Optimization & Continuous Improvement
  • Monitor model performance and recalibrate as required.
  • Identify opportunities to improve efficiency, scalability, and reliability of data solutions.
  • Stay updated with the latest trends in data science, analytics, and testing frameworks.
Required Skills & Experience
Technical Skills
  • Strong hands-on experience with Python for data analysis and modeling.
  • Proficiency in PostgreSQL, including complex queries and performance tuning.
  • Solid experience with PyTest for automated testing of data pipelines and models.
  • Experience with statistical analysis, hypothesis testing, and feature engineering.
  • Familiarity with data visualization tools (Matplotlib, Seaborn, Plotly, etc.).
Data Science Expertise
  • Experience building predictive models using machine learning techniques.
  • Knowledge of supervised and unsupervised learning algorithms.
  • Strong understanding of data preprocessing, normalization, and validation techniques.
Preferred Qualifications
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
  • Experience working with enterprise-scale or regulated environments.
  • Exposure to CI/CD pipelines for data science workflows.
  • Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.
Soft Skills & Competencies
  • Strong analytical and problem-solving mindset.
  • Excellent communication skills with the ability to explain complex concepts simply.
  • High attention to detail and commitment to data accuracy.
  • Ability to work independently and collaboratively in fast-paced environments.

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