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Oracle Data Science Jobs in Florida (NOW HIRING)

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How much do oracle data science jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for oracle data science in Florida is $42.59, according to ZipRecruiter salary data. Most workers in this role earn between $36.44 and $49.57 per hour, depending on experience, location, and employer.

What is data science in Oracle?

Data science in Oracle involves analyzing large datasets using statistical methods, machine learning, and data visualization to extract insights and support decision-making. Oracle provides tools like Oracle Data Science Cloud and integrates with platforms such as Python and R for model development and deployment.

What are some common challenges Oracle Data Science professionals face when integrating machine learning models with enterprise databases?

Oracle Data Science professionals often encounter challenges related to data compatibility, scalability, and security when integrating machine learning models with enterprise databases. Ensuring that large, complex datasets are properly pre-processed and that models are efficiently deployed within Oracle's ecosystem can require close collaboration with database administrators and IT teams. Additionally, maintaining data privacy and compliance with organizational standards often requires careful planning and ongoing monitoring. Having a strong understanding of Oracle Cloud Infrastructure and its machine learning tools can greatly ease this integration process.

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

AspectOracle Data ScienceData Analyst
Required SkillsData modeling, machine learning, SQL, Python, RData interpretation, Excel, SQL, visualization tools
Work EnvironmentTech companies, data science teams, cloud platformsBusiness units, reporting teams, analytics departments
CertificationsOracle certifications, data science certificationsNone specific, often Excel or business analytics certifications

Oracle Data Science roles focus on developing machine learning models and advanced analytics using Oracle tools and cloud platforms. Data Analysts primarily interpret data, create reports, and support decision-making with visualization and basic analytics. While both roles require SQL and data handling skills, Oracle Data Science positions demand expertise in machine learning and programming, whereas Data Analysts focus on data reporting and business insights.

Is 40 too late for data science?

Age is not a barrier to becoming an Oracle Data Science professional. Many data scientists start their careers later in life, and skills such as programming, statistics, and machine learning can be developed at any age through online courses and certifications. Employers value experience and problem-solving ability over age, making it possible to enter the field at 40 or older.

What are the key skills and qualifications needed to thrive as an Oracle Data Science professional, and why are they important?

To thrive as an Oracle Data Science professional, you need expertise in statistical analysis, machine learning, data modeling, and typically a degree in computer science, statistics, or a related field. Familiarity with Oracle Cloud Infrastructure, Oracle Machine Learning tools, SQL, and relevant certifications such as Oracle Data Science Certification are highly valuable. Strong analytical thinking, problem-solving, and effective communication skills help you translate complex data insights into actionable business strategies. These skills ensure you can leverage Oracle's platforms to derive meaningful insights and drive data-informed decision-making for organizations.

What is the salary of data scientist in Oracle?

The salary of an Oracle Data Scientist typically ranges from $90,000 to $140,000 annually, depending on experience, location, and skill set. Senior roles or those with specialized skills in machine learning and data analysis may earn higher compensation. Benefits often include health insurance, bonuses, and professional development opportunities.

What is an Oracle Data Scientist?

An Oracle Data Scientist is a professional who uses Oracle's suite of data science tools and platforms to analyze large datasets, build predictive models, and provide data-driven insights for organizations. They leverage Oracle Cloud Infrastructure, Oracle Machine Learning, and other Oracle technologies to process, visualize, and interpret data. Their role often involves collaborating with business stakeholders to solve complex problems, automate processes, and support decision-making using advanced analytics and machine learning techniques.

Is IT hard to get a job at Oracle?

Securing an Oracle Data Science position can be competitive, requiring strong skills in data analysis, machine learning, and familiarity with tools like Python and SQL. Candidates often need relevant experience, certifications, or advanced degrees, and the hiring process may include technical interviews and assessments.
What job categories do people searching Oracle Data Science jobs in Florida look for? The top searched job categories for Oracle Data Science jobs in Florida are:
Mathematical Statistician (Data Scientist) - Direct Hire

Mathematical Statistician (Data Scientist) - Direct Hire

US Department of the Treasury

Ocala, FL • On-site

$74K/yr

Other

Posted 6 days ago

New


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

235th of 692 rated public administrative organizations


Job description

WHAT IS DATA AND ANALYTICS?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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