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At Home Insurance Data Analytics Jobs (NOW HIRING)

G2.com, Inc

Data Analytics Specialist

Chicago, IL · On-site +1

$130K - $150K/yr

About G2 - Our People At G2, everything we are and what we do is grounded in our PEAK values ... About The Role The Product Data Science team is G2's centralized analytics and data science ...

Samsung SDSA

Data analytics

San Jose, CA · On-site

We are seeking a developer to join the data analytics team with at least 5 years of software ... development experience. The candidate is expected to be a self-learner as it relates to new big ...

Lennar

Director, Data & Analytics

Salem, OR · On-site

Our Associates have access to robust health insurance plans, including Medical, Dental, and Vision ... Home Purchase Discounts, and unique opportunities such as the Everyone's Included Day. At Lennar ...

Nycm

Associate Data Scientist (Hybrid)

Edmeston, NY · Hybrid

$73K - $123K/yr

Extract, clean, and prepare structured insurance data from multiple sources for analysis and modeling * Perform exploratory data analysis to identify trends, patterns, and anomalies in risk, claims ...

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At Home Insurance Data Analytics information

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How much do at home insurance data analytics jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for at home 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 an at home insurance data analytics?

An At Home Insurance Data Analytics job involves working remotely to analyze data related to insurance policies, claims, customer trends, and risk factors. Professionals in this role use statistical methods and specialized software to interpret large datasets and provide insights that help insurance companies make informed business decisions. The tasks may include data cleaning, reporting, predictive modeling, and collaborating with other teams to optimize products or processes. Working from home provides flexibility, but it also requires strong communication skills and self-motivation. This role is essential for helping insurance companies stay competitive and efficient in a data-driven industry.

What are the key skills and qualifications needed to thrive as an at home insurance data analytics professional?

To thrive in At Home Insurance Data Analytics, you need strong analytical skills, a background in statistics or mathematics, and experience with insurance data, often supported by a relevant degree. Proficiency with data analysis tools such as SQL, Python, R, and business intelligence platforms like Tableau or Power BI is typically required. Strong problem-solving, attention to detail, and effective communication skills help translate complex data insights for stakeholders. These skills ensure accurate risk assessment, data-driven decision-making, and effective remote collaboration in the insurance industry.

What types of data sources and tools will I typically work with as an at home insurance data analytics professional?

As an At Home Insurance Data Analytics professional, you'll regularly handle data from policy management systems, claims databases, customer interactions, and external risk assessment sources. You'll use tools like SQL for data extraction, Python or R for analysis, and data visualization platforms such as Tableau or Power BI to present insights. Collaboration with underwriting, claims, and IT teams is common to ensure data accuracy and actionable reporting. This role offers exposure to both structured and unstructured data, requiring a balance of technical skills and insurance industry knowledge.

What is the difference between At Home Insurance Data Analytics vs Insurance Data Analyst?

AspectAt Home Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's degree in statistics, data science, or related field; knowledge of insurance industryBachelor's degree in mathematics, statistics, or related field; industry-specific knowledge beneficial
Work EnvironmentRemote or home-based, collaborating with insurance teamsTypically office-based, but may include remote options; working with insurance data teams
Employer & Industry UsageInsurance companies, brokers, and agencies analyzing policy dataInsurance firms, consulting agencies, or analytics firms focusing on insurance data

At Home Insurance Data Analytics involves remote data analysis specifically tailored to insurance data, often with a focus on policy and claims data. Insurance Data Analysts may work in similar environments but are often based in-office and may handle broader data analysis tasks across various industries. Both roles require similar skills and education, but At Home Insurance Data Analytics emphasizes remote work within the insurance sector.

What cities are hiring for At Home Insurance Data Analytics jobs?

Cities with the most At Home 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 At Home Insurance Data Analytics jobs?

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

At Home Insurance Data Analytics jobs near you

Data Analytics Engineer

Mutual of Enumclaw Insurance Company

Enumclaw, WA • On-site

$140K - $171K/yr

Other

Re-posted 24 days ago

Job description

Overview
Founded in 1898, Mutual of Enumclaw is a people-first insurer rooted in community, recognized as Washington's Best Company to Work For for the 14th consecutive year, and proudly serving individuals, families, farms, and businesses through local independent agents across the West.
The Data Analytics Engineer bridges the gap between raw data and business insights by designing, building, and governing analytics-ready data assets across the P&C insurance value chain - Underwriting, Actuarial, Claims, Product, Distribution, and Finance - and all lines of business (Personal, Commercial, and Farm). Translating insurance business logic into governed, scalable data models, the Data Analytics Engineer partners with stakeholders to deliver trusted reporting and analytics solutions and plays a key role in advancing Mutual of Enumclaw's Snowflake-based medallion architecture and enabling data-driven decision-making across the company.
Location: Remote, with preference given to those residing in WA, OR, ID, MT, WY, AZ, or UT. (Candidates must be able to work during our core Pacific Standard Time business hours and have high-speed internet - an internet speed test is required.)
Hiring Range: $140,891 - $157,545
Salary Range: $140,891 - $171,631
*The hiring range represents Mutual of Enumclaw's current hiring pay scale for this role. Mutual of Enumclaw reserves the right to modify or update this range any time. Exact compensation may vary based on skills and experience. Compensation is only one part of our entire total rewards package. To see some of the benefits and perks we offer, please click here.
Responsibilities
Supervisory Responsibilities:
  • None.

Responsibilities:
Business Partnership & Delivery
  • Partner with stakeholders across Product, Actuarial, Underwriting, Claims, Finance, and Distribution to gather requirements and define KPIs, reporting needs, and data specifications
  • Design, build, and maintain dashboards, reports, and visualizations in Sigma, Power BI, or equivalent BI platforms that deliver trusted insights to underwriters, actuaries, claims leaders, distribution partners, and executive leadership
  • Translate business needs into scalable data solutions, dashboards, and analyses that support strategic and operational decision-making
  • Support recurring and ad hoc reporting, including financial, operational, and executive reporting

Data Modeling & Engineering
  • Design, build, and maintain data models, transformations, and semantic layers within a Snowflake-based medallion architecture
  • Develop scalable, testable data pipelines using SQL and dbt (or equivalent tools)
  • Integrate data from internal and external sources (e.g., policy systems, Salesforce, HubSpot)
  • Enable self-service analytics by designing semantic layers and certified data products that allow business users to answer their own questions without engineering intervention

Data Governance & Quality
  • Define and enforce data governance standards, including data definitions, access controls, and metadata management
  • Validate and test data outputs to ensure accuracy and reliability
  • Monitor data performance and continuously improve data products based on user feedback

Agile Delivery & Support
  • Collaborate with Product Owners and participate in Agile ceremonies (planning, refinement, sprint reviews)
  • Define acceptance criteria and deliver high-quality data products
  • Provide production support and troubleshoot data/reporting issues as needed

Qualifications
Required Skills/Abilities:
  • P&C insurance industry experience required, with demonstrated understanding of the insurance value chain from underwriting through claims and fluency in core insurance concepts, terminology, and reporting metrics.
  • Strong experience designing, building, and publishing dashboards and reports in Sigma, Power BI, or equivalent BI platforms, including data modeling for self-service consumption required
  • Strong experience with cloud data warehouses (Snowflake preferred) and transformation tools such as dbt
  • Proficiency in SQL; working knowledge of Python or similar scripting languages preferred
  • Solid understanding of dimensional modeling, ELT processes, and modern data architectures (e.g., medallion/lakehouse)
  • Experience building or migrating to a modern data platform (e.g., legacy data warehouse to Snowflake/medallion architecture) preferred.
  • Knowledge of data integration methods (APIs, flat files, semi-structured data) and cloud platforms (AWS or equivalent)
  • Strong communication skills with the ability to translate technical concepts for business audiences
  • Experience working in Agile environments

Education and Experience:
  • Bachelor's degree in data science, computer science, statistics, or a related field (or equivalent experience)
  • 5+ years of experience in data analytics, data engineering, or related roles
  • Experience working with data systems, pipelines, and reporting solutions
  • Experience in P&C insurance and familiarity with insurance data and metrics required (e.g., premium, loss, reserving)
  • Working knowledge of insurance source systems such as Guidewire (PolicyCenter, ClaimCenter, BillingCenter), POINT, Duck Creek, or equivalent policy and claims administration platforms preferred

Physical Requirements:
  • Prolonged periods of sitting at a desk and working on a computer, including video conferencing.

Apply