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Insurance Data Analytics Jobs (NOW HIRING)

Key Responsibilities Pricing & Insurance Analytics * Support pricing analyses, rate reviews ... Support data science and predictive modeling initiatives through data preparation, feature ...

Data Analytics Specialist

Crane, IN · On-site

$100K - $160K/yr

We are seeking a highly skilled Data Analytics Specialist with 2-5 years of experience in data ... Disability and life insurance * Pet insurance Note: Benefits may vary based on employment type ...

Key Responsibilities Pricing & Insurance Analytics * Support pricing analyses, rate reviews ... Support data science and predictive modeling initiatives through data preparation, feature ...

Data Analytics Specialist

Crane, IN · On-site

$100K - $160K/yr

We are seeking a highly skilled Data Analytics Specialistwith 2-5 years of experiencein data ... Disability and life insurance * Pet insurance Note: Benefits may vary based on employment type ...

Key Responsibilities Pricing & Insurance Analytics * Support pricing analyses, rate reviews ... Support data science and predictive modeling initiatives through data preparation, feature ...

Data Analytics

Boston, MA · On-site

$146K - $176K/yr

Data Analytics (State Street Bank and Trust Company; Boston, MA): Specific duties of the position ... company match; insurance coverage including basic life, medical, dental, vision, long-term ...

Key Responsibilities Pricing & Insurance Analytics * Support pricing analyses, rate reviews ... Support data science and predictive modeling initiatives through data preparation, feature ...

Data Analytics

Boston, MA · On-site

$146K - $176K/yr

Data Analytics (State Street Bank and Trust Company; Boston, MA): Specific duties of the position ... company match; insurance coverage including basic life, medical, dental, vision, long-term ...

Director, Data Analytics

Manhattan, NY · On-site

$186K - $256K/yr

American Express Company seeks Director, Data Analytics to provide data-intensive, strategic ... life insurance, and disability benefits • 20+ weeks paid parental leave for all parents ...

Health insurance, well-being programs HOW YOU WILL CONTRIBUTE TO THE TEAM Regional Adoption ... Data Analysis and Insight: 30% * Conduct in-depth data analysis and experimentation to uncover ...

Health insurance, well-being programs HOW YOU WILL CONTRIBUTE TO THE TEAM Regional Adoption ... Data Analysis and Insight: 30% * Conduct in-depth data analysis and experimentation to uncover ...

Director, Data & Analytics

Cambridge, MA · On-site

$191K - $263K/yr

We're looking for a Director, Data & Analytics to build and lead the analytics strategy that powers ... Medical, Dental, Vision, & Life insurances * Fitness & Wellness programs including a fitness ...

Director, Data & Analytics

Cambridge, MA · Hybrid

$191K - $263K/yr

We're looking for a Director, Data & Analytics to build and lead the analytics strategy that powers ... Medical, Dental, Vision, & Life insurances * Fitness & Wellness programs including a fitness ...

We're looking for a Director, Data & Analytics to build and lead the analytics strategy that powers ... Medical, Dental, Vision, & Life insurances * Fitness & Wellness programs including a fitness ...

Data Analytics

Mason, OH · On-site

$50 - $55/hr

Experience working in Healthcare, Health Insurance, Financial Services, or other highly regulated ... Data Analysis & Data Visualization. * Data Governance. * Statistical Analysis. * Power BI.

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How much do insurance data analytics jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for insurance data analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 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.

How much does an insurance data analyst make?

The average salary for an insurance data analyst typically ranges from $60,000 to $90,000 annually, depending on experience, location, and industry. Professionals with advanced skills in data visualization, statistical analysis, and tools like SQL or Python may earn higher salaries, especially in larger organizations or metropolitan areas.

Is data analytics a high paying job?

Data analytics roles, including those in insurance data analytics, are generally considered well-paying compared to many other entry-level positions. Salaries vary based on experience, skills, and location, but professionals with expertise in tools like SQL, Python, or R often earn competitive wages and have strong job growth prospects.

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 cities are hiring for Insurance Data Analytics jobs?

Cities with the most Insurance Data Analytics job openings:

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

The most popular types of Insurance Data Analytics jobs are:

What states have the most Insurance Data Analytics jobs?

States with the most job openings for Insurance Data Analytics jobs include:

Infographic showing various Insurance Data Analytics job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, and 5% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $113,873 per year, or $54.7 per hour.

Specialist, Data Analytics

Best Infosystems LLC

Blythewood, SC

$95K - $120K/yr

Contractor

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago


Job description

Specialist, Data Analytics - Technical Field Data_Blythewood, SC / Columbia, SC_Full-Time(FTE)_Direct Hire

Hi,
Trust this finds you well!
We've spotted your impressive profile and have an exciting opportunity tailored to your skills and passions.

Position Title: Specialist, Data Analytics - Technical Field Data
Job Type: Full-Time
Location: Blythewood, SC / Columbia, SC
Base Salary: $95,000 to $120,000 + Best-in-class benefits
Industry: Automotive
Job Category: Information Technology - Quality Assurance

Job Description:
Field Issue Detection & Resolution
* Support end-to-end root cause analysis (RCA) of customer issues across full vehicle systems, including powertrain, high-voltage battery, and connected features
* Identify patterns in fleet data to enable early detection of emerging quality issues
* Drive faster resolution through data-driven insights and cross-functional collaboration

Data Strategy & Analytics:
* Define and implement strategies for collecting, organizing, and analyzing large-scale connected vehicle data
* Partner with engineering teams to establish vehicle data policies, signal strategies, and telemetry requirements
* Perform advanced data analysis to correlate vehicle behavior, software versions, and customer-reported issues

AI/ML & Advanced Analytics

Develop and deploy AI/ML models for:
* Anomaly detection
* Failure prediction
* Sentiment analysis

Leverage analytics to improve customer satisfaction, reliability, and warranty performance

Data Management & Integration:
* Act as the bridge between software-defined vehicle data policies and real-world engineering insights
* Ensure data pipelines are robust, accurate, and actionable
* Enable a VIN-level (Vehicle 360) view for comprehensive lifecycle traceability

Cross-Functional Collaboration

Work closely with:
* Vehicle engineering (hardware & software)
* Connected vehicle and app development teams
* Service, warranty, and customer support organizations

Enhance data collection capabilities, user interfaces, and reporting standards across systems

Customer Insight & Voice of Customer (VoC)
* Serve as a VoC quality expert, ensuring timely and accurate feedback loops into engineering
* Design and implement customer surveys and feedback frameworks to assess product satisfaction
* Analyze large volumes of unstructured data (social media, web forums, call center logs, customer verbatims) to identify key customer pain points and trends

Location & Travel Expectations:
* This role requires In-Person Attendance: Daily / Mutually agreed with Manager


What you’ll bring 
* Education/Certifications: A bachelor’s degree in engineering, computer science and/or data science.
* Years of Experience: 5+ years in an environment related to technical data processing, preferably within a vehicle manufacturer or supplier environment. Relevant experience in other sectors will also be considered.
* Experience in automotive engineering, quality, or field issue analysis, ideally in EV or connected vehicle environments is preferred. 
* Experience from non-automotive would also be acceptable with the ability to absorb meta data to perform root cause analysis.
* Hands-on experience with data analytics tools and large datasets (e.g., Databricks, SQL, Python, cloud platforms)
* Experience in running Java Script, Python, SQL, HTML/CSS
* Experience in deploying AI-based solutions and tools for data processing. Ability to build full-scale AI-powered products from scratch using available open AI
* Familiarity with AI/ML concepts and applications in anomaly detection or predictive analytics
* Understand data warehouse systems like Basic AWS or Azure data services or Databricks. Ability to support enterprise projects on as need basis.
* Ability to work across functions and translate data insights into engineering actions
* Experience with PBI and PowerApps, building app own-made solutions for data analytics.
* Strong interpersonal skills, with experience working in multicultural and team-oriented environments.

Competitive insurance including:
*Medical, dental, vision and income protection plans
401(k) program with:
*An employer match and immediate vesting
Generous Paid Time Off including:
*20 days planned PTO, as accrued
*40 hours of unplanned PTO and 14 company or floating holidays, annually
*Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders
*Paid leave for circumstances related to bereavement, jury duty, voting time, or military leave

Pay Transparency:
*This is a full-time, exempt position eligible to receive a base salary and to participate in an annual performance bonus program. Final salary offered will be determined based on factors including but not limited to the candidate's skills and experience. The annual performance bonus program is preset and not candidate dependent.

*Initial Base Salary Range: $95,000.00 - $120,000.00

*Internal Leveling Code: IC9

Notice to applicants:

* Residing in New York City: This role is not eligible for remote work in New York City.

Skills and Certifications:
*Bachelor degree in engineering, computer science or data science
*Hands-on experience with data analytics tools and large datasets (e.g., Databricks, SQL, Python, clo
*Experience in running Java Script, Python, SQL, HTML/CSS
*Experience in deploying AI-based solutions and tools for data processing.
*Experience in an environment related to technical data processing.

Compensation:
*Full-time
*Benefits - Full
*Relocation Assistance Available - Yes
*Bonus Eligible - Yes

Candidate Details:
*5+ to 7 years experience
*Seniority Level - Mid-Senior
*Minimum Education - Bachelor's Degree
*Willingness to Travel - Occasionally

Ideal Candidate:
*Ideal Candidate Profile: Specialist, Data Analytics - Technical Field Data

*The ideal candidate is a highly analytical and technically skilled data professional who excels at transforming large volumes of complex vehicle, customer, and operational data into actionable insights. 
*They have experience supporting product quality, engineering, warranty, or field performance functions and can connect data patterns to real-world customer and vehicle issues. 
*This individual thrives in fast-paced environments, enjoys solving difficult problems, and can bridge the gap between data science, engineering, quality, and customer experience teams.
Background & Experience

* 5+ years of experience in technical data analytics, field quality, engineering analytics, reliability engineering, or connected vehicle data analysis.
* Experience within automotive OEMs, EV manufacturers, Tier 1 suppliers, mobility companies, or other industries involving large-scale IoT/telemetry data.
* Proven ability to analyze field performance data and identify trends, anomalies, and emerging product concerns.
* Experience supporting product quality investigations, warranty analytics, root cause analysis, or reliability improvement initiatives.
* Exposure to connected vehicles, software-defined products, batteries, powertrain systems, or highly complex technical products is preferred.

Technical Expertise:
The strongest candidates will possess advanced proficiency in:

* SQL
* Python
* Databricks
* Power BI
* Cloud platforms (AWS, Azure)
* Data Warehousing and ETL concepts
* Data visualization and reporting

Additionally, they should have experience with:

* AI/ML model development and deployment
* Predictive analytics
* Anomaly detection
* Sentiment analysis
* Data pipeline development
* Telemetry and IoT data processing
* Power Apps application development
* JavaScript, HTML/CSS for custom analytical tools and dashboards

Automotive & Vehicle Analytics Knowledge

A standout candidate understands how vehicle systems operate and can connect data signals to engineering outcomes. They have experience analyzing:

* Connected vehicle telemetry
* Vehicle software performance
* High-voltage battery systems
* Powertrain data
* Vehicle diagnostics
* Service and warranty claims
* Customer-reported concerns
* Fleet performance metrics

They can identify patterns across thousands of vehicles and determine whether an issue stems from software, hardware, manufacturing variation, customer usage, or environmental conditions.
AI & Advanced Analytics Capabilities

The ideal candidate is not simply a reporting analyst. They actively leverage AI and machine learning to improve business outcomes.

They should be capable of:
* Building predictive maintenance and failure prediction models.
* Developing anomaly detection algorithms.
* Applying NLP and sentiment analysis to customer feedback.
* Creating AI-powered tools that automate issue detection and investigation.
* Designing scalable analytical solutions that support engineering and quality teams.

Experience building AI-enabled applications using modern AI platforms and OpenAI technologies would be highly attractive.
Voice of Customer (VoC) & Customer Insights

Top candidates understand that product quality extends beyond engineering data.

They have experience analyzing:
* Customer surveys
* Social media feedback
* Online forums
* Call center logs
* Warranty comments
* Customer verbatims

They can synthesize technical and customer data into a comprehensive understanding of field performance and customer satisfaction.
Cross-Functional Leadership

The ideal candidate is an influential collaborator who can work effectively with:
* Vehicle Engineering
* Software Engineering
* Connected Vehicle Teams
* Quality Organizations
* Service Operations
* Warranty Teams
* Customer Experience Teams
* Data Engineering Groups

They can translate technical findings into clear recommendations, helping leadership prioritize corrective actions and product improvements.

Soft Skills & Behavioral Traits:
The successful candidate will be:
* Naturally curious and investigative
* Comfortable working in ambiguity
* Data-driven and fact-based
* Able to communicate complex findings to non-technical audiences
* Highly organized and detail-oriented
* Self-directed and capable of working independently
* Comfortable challenging assumptions with evidence
* Passionate about improving products and customer experiences

Preferred Experience:
Highly competitive candidates may have:
* Automotive OEM or Tier 1 experience
* Connected vehicle analytics experience
* Reliability engineering experience
* Vehicle diagnostics and telematics expertise
* Warranty analytics experience
* Advanced machine learning and AI implementation experience
* Experience supporting greenfield manufacturing or product launches
========
Screening Questions:

# Does the candidate have a minimum of Bachelor's degree?
# Does the candidate have 5+ years of experience with technical data processing?
# Does the candidate have automotive industry experience?
# Is the candidate willing to relocate to Columbia, SC?
# Will the candidate require sponsorship now or in the future?
# Does the approved salary range align with the candidates expectations?
# What is the reason for seeking change from your current role?
# What is your annual base salary expectations (USD)?
# Preferred location - Blythewood, SC / Columbia, SC (Onsite):
# Current Location, State with zip code:
# Work authorization for working in USA (USC / GC):