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Insurance Data Analytics Jobs in Miami, FL (NOW HIRING)

Corient Services LLC

Data Analyst

Miami, FL · On-site

$70 - $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

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

$75 - $120/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 ...

eMed LLC

Analytics Engineer

Miami, FL · On-site

Data & Analytics About eMed eMed is a digital-health company built on its Empathetic AI™ ... Life Insurance (Basic, Voluntary & AD&D) * Paid Time Off * Short Term & Long Term Disability

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All JobsInsurance Data Analytics JobsInsurance Data Analytics Jobs in Miami, FL

Insurance Data Analytics information

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$23

$52

$90

How much do insurance data analytics jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for insurance data analytics in Miami, FL is $52.36, according to ZipRecruiter salary data. Most workers in this role earn between $42.07 and $59.33 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 Miami, FL?

The most popular types of Insurance Data Analytics jobs in Miami, FL are:

What are popular job titles related to Insurance Data Analytics jobs in Miami, FL?

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

What job categories do people searching Insurance Data Analytics jobs in Miami, FL look for?

The top searched job categories for Insurance Data Analytics jobs in Miami, FL are:

What cities near Miami, FL are hiring for Insurance Data Analytics jobs?

Cities near Miami, FL with the most Insurance Data Analytics job openings:

Insurance Data Analytics jobs near you
Infographic showing various Insurance Data Analytics job openings in Miami, FL as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 16% Part Time, and 5% Contract. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $108,913 per year, or $52.4 per hour.

Data Analytics Engineer

Coral Gables, FL • On-site

Lakeview Loan Servicing
51 - 200 employees
Learn more about Lakeview Loan Servicingexternal

$118K - $130K/yr

Full-time

Posted 4 days ago

Job description

Overview
Lakeview Household Insurance Solutions (LHIS) is the insurance brokerage arm of Lakeview Loan Servicing, offering P&C personal lines of insurance to approximately 3 million mortgage customers serviced by Lakeview Loan Servicing. The pay range for this position is $118,000-$130,000
The Data Analytics Engineer is responsible for designing and maintaining the analytical data structures, semantic models, reporting datasets, and data governance processes that support trusted business intelligence across LHIS. Working within the Business Intelligence function, this role serves as a key owner of data quality, analytical architecture, and reporting enablement across multiple business domains.
The Data Analytics Engineer partners closely with Sales, Marketing, Operations, Technology, and Data Engineering to ensure operational processes are structured to support accurate reporting, while developing and maintaining analytical models within Microsoft Fabric. Particular emphasis is placed on sales and customer lifecycle data, ensuring operational systems produce reliable and analytically useful information from the point of collection through final reporting and KPI delivery.
Responsibilities
Data Governance & Process Design
  • Partner with business leaders to ensure operational processes capture accurate, complete, and reportable data.
  • Recommend improvements to workflows, field structures, stage definitions, and business processes to improve reporting accuracy and data quality.
  • Establish and maintain standards for data governance, field usage, and business definitions.
  • Identify gaps in data collection and implement solutions that improve analytical visibility.
  • Audit operational data and system usage to ensure consistency across departments.
  • Serve as the primary analytical stakeholder for business process and data structure decisions, ensuring changes to operational systems support both business execution and future reporting requirements.

Analytics Architecture & Semantic Modeling
  • Design and maintain semantic models within Microsoft Fabric to support enterprise reporting and analytics.
  • Develop analytical datasets and business logic required for reporting and performance measurement.
  • Translate operational business processes into scalable analytical models.
  • Apply dimensional modeling principles, including Kimball methodologies, fact tables, and dimension tables, to support reporting, dashboarding, and future analytical initiatives.
  • Partner with Data Engineering to ensure source data is available and properly structured for analytical consumption.
  • Support the ongoing development and enhancement of the Business Intelligence layer and contribute to scalable reporting frameworks capable of supporting future organizational growth.

Reporting, Business Intelligence & Data Quality
  • Define, document, and maintain KPI calculations and business metric definitions.
  • Validate reporting outputs against operational expectations and business requirements.
  • Support dashboard development and ad hoc analytical initiatives for Sales, Marketing, and Operations.
  • Develop reconciliation processes and data quality controls, including monitoring, validation, and issue resolution, to improve trust in reporting.
  • Collaborate with stakeholders to ensure reporting solutions support business objectives and improve data capture outcomes.
  • Identify opportunities for advanced analytics as organizational data maturity increases.

Qualifications
The job requires regular sitting and use of hands for handling objects, tools, or controls, with frequent talking and listening in a moderately noisy environment. There will be occasional standing, walking, and reaching with hands and arms, with rare instances of stooping, kneeling, crouching, or crawling. Lifting and moving objects up to 10 pounds is a regular part of the role. Specific vision abilities such as close vision, color vision, and the ability to adjust focus are necessary.
Additionally, the employee must connect to the internet via a direct Ethernet connection, maintain a dedicated workspace to safeguard customer information, and have an internet connection with a minimum download speed of 50 Mbps and a minimum upload speed of 10 Mbps. If using shared internet, prioritizing the connection for work purposes is strongly recommended, with the preference for a dedicated connection solely for work-related tasks.
EEOC
Lakeview Household Insurance Solutions is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.
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