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Insurance Data Analytics Jobs in Florida (NOW HIRING)

Corient Services LLC

Data Analyst

Miami, FL · On-site

$80 - $100/hr

Develop and maintain data analytics solutions focused on enabling decision making, optimization ... Employer paid Dental, Vision & Life and AD&D Insurance * Employer paid Short-term & Long-term ...

Ci

Data Analyst

Miami, FL · On-site

Ad-hoc analytics and insights . Promptly address ad-hoc analysis requests with clear, well ... Employer paid Dental, Vision & Life and AD&D Insurance * Employer paid Short-term & Long-term ...

Corient

Data Analyst

Miami, FL · On-site

$80 - $100/hr

Develop and maintain data analytics solutions focused on enabling decision making, optimization ... Employer paid Dental, Vision & Life and AD&D Insurance * Employer paid Short-term & Long-term ...

Collabera LLC

Associate Data Analyst

Orlando, FL · On-site

$22 - $24/hr

Experience or coursework in financial services, retail banking, data analytics, controls testing ... insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term ...

Apex Systems

Data Analyst

Juno Beach, FL · On-site

Experience related to data analytics for renewable power plants is required. Experience with Agile ... other insurance plans that offer an optional layer of financial protection. We offer an ESPP ...

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How much do insurance data analytics jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for insurance data analytics in Florida is $40.91, according to ZipRecruiter salary data. Most workers in this role earn between $32.88 and $46.35 per hour, depending on experience, location, and employer.

What is insurance data analytics?

An Insurance Data Analytics job involves analyzing large volumes of insurance-related data to identify trends, assess risks, detect fraud, and improve decision-making. Professionals in this field use statistical models, machine learning, and data visualization tools to extract insights that help insurers optimize pricing, enhance customer experience, and reduce losses. They work with claims data, policyholder information, and external data sources to drive business strategy. Strong analytical skills, proficiency in data tools like SQL, Python, or R, and knowledge of insurance principles are essential for success in this role.

What are the typical responsibilities of someone working in insurance data analytics?

Professionals in Insurance Data Analytics are responsible for collecting, cleaning, and analyzing large sets of insurance-related data to identify trends, assess risk, and inform business decisions. They commonly develop predictive models, generate reports, and provide actionable insights that help underwriting teams, actuarial staff, and business leaders optimize processes or pricing strategies. Day-to-day tasks may also include collaborating with IT and business units to define data requirements, presenting findings to non-technical stakeholders, and ensuring data integrity. This role often involves a mix of independent analysis and team-oriented projects, offering a dynamic and engaging work environment for problem solvers.

What are the key skills and qualifications needed to thrive in insurance data analytics?

To thrive in Insurance Data Analytics, you need a solid understanding of data analysis, statistics, and insurance industry concepts, usually supported by a degree in mathematics, statistics, finance, or a related field. Proficiency with analytical tools like SQL, Python, R, and data visualization platforms (such as Tableau or Power BI), as well as certifications like CPCU or advanced analytics credentials, are highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts translate complex data into actionable business insights. These skills are crucial for driving informed decision-making, risk assessment, and operational improvements within insurance organizations.

How is data analytics used in insurance?

In insurance, data analytics is used by professionals to assess risk, set premiums, detect fraud, and improve customer segmentation. Analysts utilize tools like statistical models and machine learning algorithms to interpret large datasets, enabling more accurate underwriting and claims management. Strong analytical skills and knowledge of data visualization are essential for effective decision-making in this field.

What does a data analyst do in insurance?

An insurance data analyst examines large datasets to identify trends, assess risk, and support decision-making processes within insurance companies. They use tools like Excel, SQL, and data visualization software to interpret claims, policy data, and customer information, helping improve underwriting, pricing, and fraud detection.

What are the most commonly searched types of Insurance Data Analytics jobs in Florida?

The most popular types of Insurance Data Analytics jobs in Florida are:

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

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

What job categories do people searching Insurance Data Analytics jobs in Florida look for?

The top searched job categories for Insurance Data Analytics jobs in Florida are:

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

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

Insurance Data Analytics jobs near you
Infographic showing various Insurance Data Analytics job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, and 4% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $85,097 per year, or $40.9 per hour.

SENIOR DATA ANALYST

ONE ALLIANCE INSURANCE MANAGERS INC

Orlando, FL • On-site

$80K - $101K/yr

Full-time

Re-posted 6 days ago

Job description

General Description:

The Senior Data Analyst is responsible for leading advanced reporting, analytics, and business intelligence initiatives within the Information Technology organization. This role partners closely with executive leadership, business stakeholders, and data engineering teams to deliver high-impact analytical solutions that drive operational performance, strategic decision-making, and enterprise growth.

The Senior Data Analyst designs scalable reporting frameworks, develops enterprise-grade dashboards and paginated reports, and performs advanced data analysis using modern tools and statistical techniques. This position serves as a subject matter expert in SQL Server, Power BI, and data modeling, while mentoring junior analysts and promoting data governance, automation, and analytical best practices.

 

Essential Duties and Responsibilities:

Enterprise Reporting & Business Intelligence

  • Lead development of executive dashboards and operational reporting solutions using Power BI and Power BI Paginated Reports
  • Design scalable semantic models (star schema, dimensional modeling) aligned with enterprise data standards
  • Deliver daily, weekly, monthly, and ad-hoc reporting with a focus on automation, accuracy, and performance
  • Ensure consistency and reconciliation across financial, underwriting, claims, sales, and operational reports

Advanced Data Analysis

  • Perform complex data analysis using SQL Server, Python (pandas, NumPy), and statistical techniques
  • Identify trends, patterns, anomalies, and business drivers within large datasets
  • Translate business questions into structured analytical approaches and actionable insights
  • Develop data validation and reconciliation processes to improve trust in enterprise reporting

Data Modeling & Query Optimization

  • Write advanced T-SQL queries, views, and stored procedures optimized for performance
  • Collaborate with Data Engineering on data models and data product design
  • Optimize report performance through indexing strategies, query tuning, and model design improvements

Automation & Process Improvement

  • Automate recurring reports and analytical workflows
  • Replace manual Excel-based processes with scalable BI solutions
  • Implement quality checks and monitoring processes to reduce reporting risk

Strategic Partnership

  • Serve as analytical advisor to department leaders and executives
  • Participate in requirements gathering sessions and translate business needs into technical deliverables
  • Present findings clearly to both technical and non-technical audiences
  • Contribute to roadmap discussions for analytics platform modernization

Mentorship & Governance

  • Mentor junior analysts on SQL, data modeling, visualization best practices, and documentation standards
  • Promote consistent definitions, KPIs, and metadata usage across departments
  • Contribute to documentation, wiki content, and data dictionary standards

Additional Responsibilities

  • Contribute to project planning and task tracking
  • Successfully manage multiple initiatives simultaneously
  • Perform other duties as required

Education and/or Experience:

  • Bachelor’s degree in Information Systems, Computer Science, Data Analytics, or related discipline required
  • 6+ years of progressive experience in data analysis, business intelligence, or analytics roles
  • Advanced proficiency in Microsoft SQL Server (T-SQL, stored procedures, query optimization)
  • Strong expertise in Power BI (data modeling, DAX, report design, paginated reports)
  • Experience designing dimensional data models (fact/dimension tables, star schema)
  • Proficiency in Python for data analysis (pandas, NumPy; scikit-learn a plus)
  • Experience with Azure-based data environments and modern data platforms preferred
  • Strong understanding of data quality validation, reconciliation, and governance practices
  • Familiarity with Machine Learning concepts and predictive modeling methodologies preferred
  • Experience working in Property & Casualty Insurance a must
  • Familiarity with ticketing systems used to assign and track work
  • Strong written and oral communication skills