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Insurance Data Processing Jobs in Florida (NOW HIRING)

Jr. Data Analyst (part-time)

Tampa, FL · On-site

$53K - $113K/yr

Identify data quality issues, inconsistencies, and processing errors, and help resolve them ... We offer a comprehensive package of benefits including paid time off, health and welfare insurance ...

Benefits include medical, dental, and vision insurance, 401(k) retirement plan, paid time off, paid ... Process and analyze large-scale geospatial datasets * Create data visualization and reporting ...

Data Engineer - Databricks

Tampa, FL · Hybrid

$108K - $129K/yr

Performance tuning for large-scale data processing * Data security and privacy best practices ... Company Paid Medical Insurance Option for Employee and Dependent Children * Company Paid Dental ...

Data Engineer - Databricks

Tampa, FL · On-site

$108K - $129K/yr

Performance tuning for large-scale data processing * Data security and privacy best practices ... Company Paid Medical Insurance Option for Employee and Dependent Children * Company Paid Dental ...

Design, develop, and maintain data pipelines and ETL processes. * Ensure data quality and integrity ... other insurance plans that offer an optional layer of financial protection. We offer an ESPP ...

Insurance experience is highly preferred. * Solid foundation in data structures, algorithms, and system design. * Experience with modern data storage, messaging, and processing tools (e.g., SQL ...

Senior Data Analyst

Juno Beach, FL · On-site

$84K - $106K/yr

Senior Data Analyst will design, develop, and maintain data pipelines and ETL processes * Ensure ... We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and ...

Data Solutions Engineer

Orlando, FL · On-site

$106K - $128K/yr

RESPONSIBILITIES: • Develop and implement data processing workflows and pipelines to support ... Life Insurance * Voluntary Accident Insurance - Self and Family * Short and Long-Term Disability

Data Engineer

Okaloosa Island, FL · On-site

$79K - $134K/yr

Experience with data processing frameworks such as Apache Kafka, Fivetran * Experience in building ... insurance; health savings accounts; a 401(k) savings plan; disability coverage; and life and ...

Data Engineer

Fort Walton Beach, FL · Remote

$79K - $134K/yr

Experience with data processing frameworks such as Apache Kafka, Fivetran * Experience in building ... insurance; health savings accounts; a 401(k) savings plan; disability coverage; and life and ...

Data Engineer

Fort Walton Beach, FL · Remote

$79K - $134K/yr

Experience with data processing frameworks such as Apache Kafka, Fivetran * Experience in building ... insurance; health savings accounts; a 401(k) savings plan; disability coverage; and life and ...

Senior Data Systems Analyst

Jacksonville, FL · Remote

$79K - $100K/yr

Business Process Validation * Insurance industry experience (P&C and/or Life Insurance). * Experience supporting enterprise data warehouse environments. Demonstrated Expertise In: * Data quality ...

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Insurance Data Processing information

What is insurance data processing?

Insurance Data Processing refers to the collection, entry, management, and analysis of data related to insurance policies, claims, customers, and transactions. Professionals in this field use specialized software and systems to ensure that insurance information is accurate, up-to-date, and secure. Their work supports the smooth operation of insurance companies by helping to process claims, issue policies, and generate reports for decision-making. Accuracy and attention to detail are crucial in this role due to the sensitive nature of insurance data.

What are the key skills and qualifications needed to thrive as an insurance data processing specialist?

To thrive as an Insurance Data Processing Specialist, you need strong attention to detail, proficiency in data entry, and a solid understanding of insurance terminology, typically supported by a high school diploma or relevant associate degree. Familiarity with insurance management software, claims processing systems, and database tools such as Microsoft Excel is commonly required. Excellent organizational skills, problem-solving abilities, and effective communication help you excel in managing large volumes of sensitive information. These skills ensure accuracy, minimize errors, and support efficient operations within insurance organizations.

What are some common challenges faced in an insurance data processing role and how can they be addressed?

One of the main challenges in Insurance Data Processing is managing large volumes of sensitive data accurately and efficiently, especially when dealing with tight deadlines and evolving regulatory requirements. Errors in data entry or processing can impact claims or policy management, making attention to detail and strong organizational skills essential. To address these challenges, many teams rely on robust data management software, regular training, and collaborative workflows to ensure accuracy and compliance. Proactively seeking feedback and staying updated on industry best practices can also help professionals excel in this role.

What is the difference between Insurance Data Processing vs Insurance Claims Processing?

AspectInsurance Data ProcessingInsurance Claims Processing
Required CredentialsTypically high school diploma or equivalent; some roles may require certifications in data managementHigh school diploma or equivalent; often requires knowledge of claims procedures and insurance policies
Work EnvironmentOffice setting, working with databases and data entry systemsOffice environment, interacting with claim documents and insurance systems
Employer & Industry UsageInsurance companies, third-party administrators, data service providersInsurance companies, claims adjusters, third-party claims processors

Insurance Data Processing involves managing and organizing insurance-related data, focusing on data accuracy and database management. Insurance Claims Processing centers on evaluating and processing insurance claims submitted by policyholders, ensuring proper documentation and compliance. While both roles support insurance operations, Data Processing emphasizes data management, whereas Claims Processing focuses on claim evaluation and settlement.

What are popular job titles related to Insurance Data Processing jobs in Florida?

For Insurance Data Processing jobs in Florida, the most frequently searched job titles are:

What cities in Florida are hiring for Insurance Data Processing jobs?

Cities in Florida with the most Insurance Data Processing job openings:

Infographic showing various Insurance Data Processing job openings in Florida as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, and 4% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.

Jr. Data Analyst (part-time)

Tampa, FL • On-site

$53K - $113K/yr

Part-time

Medical, Retirement, PTO

Posted 4 days ago


Job description

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what's happening now and shape what's coming next. Vantor is a place for problem solvers, changemakers, and go-getters-where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world.
To be eligible for this position, you must be a U.S. Person, defined as a U.S. citizen, permanent resident, Asylee, or Refugee.
Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).
Please review the job details below.
Vantor is seeking a motivated, detail-oriented Junior Data Analyst to support data ingestion, processing, quality control, and workflow automation activities in Tampa. The successful candidate will assist with developing and maintaining Python-based tools that transform raw data into organized, usable information for analysis and reporting.
This position is well suited for an early-career professional with an interest in data analytics, automation, artificial intelligence, and geospatial intelligence. The candidate should be comfortable learning new technologies, working independently, documenting processes, and collaborating with technical and mission-focused team members.
Key Responsibilities
  • Develop and maintain Python scripts for automated data ingestion, processing, transformation, and quality control.
  • Organize and validate structured and unstructured data from multiple sources.
  • Assist with automating repetitive data-handling and reporting tasks.
  • Identify data quality issues, inconsistencies, and processing errors, and help resolve them.
  • Support the use of APIs, file-based workflows, databases, and other data sources.
  • Apply large language models (LLMs) and AI-enabled tools to support data processing, classification, summarization, and workflow automation.
  • Document scripts, data workflows, procedures, and results.
  • Support analysts and technical staff with data preparation and basic troubleshooting.
  • Maintain a high level of accuracy, organization, and confidentiality.

Basic Qualifications
  • Experience with Python, including scripting for data manipulation and automation.
  • Familiarity with automated data ingestion and data processing workflows.
  • Basic understanding of data structures, file formats, and quality-control methods.
  • Experience using tools such as pandas, NumPy, or similar Python libraries.
  • Experience using LLMs or AI-enabled tools for analysis, automation, or productivity is preferred.
  • Strong attention to detail and problem-solving skills.
  • Ability to work independently for a part-time schedule of approximately 20 hours per week.
  • Strong written and verbal communication skills.
  • Must be located in or able to work from the Tampa, Florida area.

Preferred Qualifications
  • Coursework, internship, or project experience in data science, computer science, information systems, engineering, or a related field.
  • Familiarity with SQL, APIs, Git, Jupyter Notebooks, or cloud-based data environments.
  • Experience with geospatial data, satellite imagery, remote sensing, or geographic information systems.
  • Exposure to machine learning, prompt engineering, or AI-assisted data workflows.

Pay Transparency: In support of pay transparency at Vantor, we disclose salary ranges on all U.S. job postings. The successful candidate's starting pay will fall within the salary range provided below and is determined based on job-related factors, including, but not limited to, the experience, qualifications, knowledge, skills, geographic work location, and market conditions. Candidates with the minimum necessary experience, qualifications, knowledge, and skillsets for the position should not expect to receive the upper end of the pay range.
The base pay for this position ranges from our lowest geographic market up to our highest geographic market within California, Colorado, District of Columbia, Hawaii, Illinois, Maryland, Minnesota, New Jersey, New York, and Washington:$53,000.00 - $113,000.00 annually.
We offer a comprehensive package of benefits including paid time off, health and welfare insurance, and 401(k) to eligible employees. You can find more information on our benefits at: https://www.vantor.com/careers
The application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire.
The date of posting can be found on Vantor's Career page at the top of each job posting.
To apply, submit your application via Vantor's Career page.
Vantor values diversity in the workplace and is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.