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Insurance Data Analytics Jobs in Brooklyn, NY (NOW HIRING)

1 point system

Insurance Data Analyst

New York, NY · Remote

Required Qualifications * 5+ years of experience working with insurance bordereaux (BDX) reporting, premium reporting, or insurance data analysis. * Strong understanding of MGA, Program, P&C, or ...

Novella

Insurance Data Scientist

New York, NY · On-site

Hands-on experience with insurance loss data, loss development, exposure analysis, and rate adequacy. * Experience building models that have been deployed in production and used to make real ...

EPIC Brokers

Lead Insurance Data Scientist

Summit, NJ · On-site

$150/hr

There are many reasons why EPIC Insurance Brokers & Consultants has become one of the fastest ... Join our Enterprise Data & Analytics team and play a central role in advancing data analysis ...

Selective Insurance

Data & Analytics Architect

Short Hills, NJ · On-site

$69.25 - $89.25/hr

Selective Insurance is a midsized U.S. domestic property and casualty insurance company with a strong financial performance history. The Data and Analytics Architect will be responsible for designing ...

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Insurance Data Analytics information

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How much do insurance data analytics jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for insurance data analytics in Brooklyn, NY is $57.57, according to ZipRecruiter salary data. Most workers in this role earn between $46.25 and $65.19 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 Brooklyn, NY?

The most popular types of Insurance Data Analytics jobs in Brooklyn, NY are:

What are popular job titles related to Insurance Data Analytics jobs in Brooklyn, NY?

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

What job categories do people searching Insurance Data Analytics jobs in Brooklyn, NY look for?

The top searched job categories for Insurance Data Analytics jobs in Brooklyn, NY are:

What cities near Brooklyn, NY are hiring for Insurance Data Analytics jobs?

Cities near Brooklyn, NY with the most Insurance Data Analytics job openings:

Insurance Data Analytics jobs near you
Infographic showing various Insurance Data Analytics job openings in Brooklyn, NY as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, and 5% Contract. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $119,738 per year, or $57.6 per hour.

Insurance Data Analyst

1 point system

New York, NY • Remote

Contractor

Re-posted 15 days ago

Job description

Required Qualifications

  • 5+ years of experience working with insurance bordereaux (BDX) reporting, premium reporting, or insurance data analysis.
  • Strong understanding of MGA, Program, P&C, or Specialty Insurance operations.
  • Advanced SQL skills, including data extraction, joins, aggregations, and reconciliation analysis.
  • Experience analyzing policy, premium, and claims data.
  • Strong Excel skills, including PivotTables, VLOOKUP/XLOOKUP, and data validation techniques.
  • Experience identifying and resolving data quality issues.
  • Excellent analytical, problem-solving, and communication skills.