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Remote Insurance Data Analytics Jobs in Idaho (NOW HIRING)

... Insurance, Transportation & Logistics, Energy & Utilities, Healthcare & Life Sciences, Government ... Analytics (Data Architecture, Data Engineering, Data Migration, Data Modernization, Big Data ...

SEO Analyst

Post Falls, ID · On-site +1

$85K/yr

Overview As an SEO Analyst, your role is to make meaning out of messy data and help shape smarter ... This is a remote position. Our main office is in Spokane, WA, and we have satellite offices in ...

The Design Engineer exercises discretion in selecting analytical methods, interpreting data, and ... This role is remote, with the expectation that candidates are located within a reasonable driving ...

Partner with leadership to ensure financial data is audit-ready and decision-ready at all times ... insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits ...

Partner with leadership to ensure financial data is audit-ready and decision-ready at all times ... insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits ...

Reviewing credit requests through standardized processes that analyze financial data, debt-to ... The working conditions will vary between an office environment and a remote home environment. The ...

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Remote Insurance Data Analytics information

What is the difference between Remote Insurance Data Analytics vs Remote Insurance Underwriter?

AspectRemote Insurance Data AnalyticsRemote Insurance Underwriter
Required CredentialsBachelor's in Data Science, Statistics, or related field; often certifications in data analysis or analyticsBachelor's in Business, Finance, or related; often requires insurance licensing or certifications
Work EnvironmentPrimarily data analysis, modeling, and reporting; often collaborative with IT and actuarial teamsAssessing risks, reviewing applications, making underwriting decisions; involves communication with agents and clients
Employer & Industry UsageUsed across insurance companies, reinsurers, and brokers for data-driven decision makingUsed by insurance carriers to evaluate and approve policies

Remote Insurance Data Analytics focuses on analyzing insurance data to inform business decisions, while Remote Insurance Underwriters evaluate individual insurance applications to determine coverage. Both roles are essential in the insurance industry but differ in daily tasks and required skills.

What is remote insurance data analytics?

Remote insurance data analytics is the practice of analyzing insurance-related data, such as claims, risk assessments, and customer information, from a location outside of a traditional office setting. Professionals in this field use statistical methods, data mining, and machine learning tools to identify patterns, detect fraud, and help insurance companies make data-driven decisions. This remote role often requires proficiency in data analysis tools like SQL, Python, or R, and a strong understanding of insurance industry concepts. Remote insurance data analysts collaborate with teams virtually to provide insights and support business strategies, making it a flexible career option.

How do Remote Insurance Data Analytics professionals typically collaborate with cross-functional teams to drive business insights?

Remote Insurance Data Analytics professionals often work closely with underwriters, actuaries, claims managers, and IT teams to gather data requirements, interpret findings, and implement data-driven solutions. Collaboration usually happens through virtual meetings, collaborative dashboards, and project management tools to ensure clear communication and alignment on objectives. This cross-functional approach helps identify trends, optimize risk assessments, and support strategic decision-making within the organization. Building strong relationships with team members across departments is key to successfully translating analytical results into actionable business strategies.

What are the key skills and qualifications needed to thrive as a Remote Insurance Data Analytics professional, and why are they important?

To excel in Remote Insurance Data Analytics, you need strong analytical skills, a background in statistics or mathematics, and typically a degree in data science, actuarial science, or a related field. Familiarity with data analysis tools like SQL, Python, R, and specialized insurance analytics platforms such as SAS or Tableau, as well as relevant certifications, is highly valuable. Attention to detail, problem-solving abilities, and effective communication set candidates apart in this role. These skills are crucial for transforming complex insurance data into actionable insights that drive informed business decisions and risk assessments.
What are the most commonly searched types of Insurance Data Analytics jobs in Idaho? The most popular types of Insurance Data Analytics jobs in Idaho are:
What are popular job titles related to Remote Insurance Data Analytics jobs in Idaho? For Remote Insurance Data Analytics jobs in Idaho, the most frequently searched job titles are:
What job categories do people searching Remote Insurance Data Analytics jobs in Idaho look for? The top searched job categories for Remote Insurance Data Analytics jobs in Idaho are:
What cities in Idaho are hiring for Remote Insurance Data Analytics jobs? Cities in Idaho with the most Remote Insurance Data Analytics job openings:
Infographic showing various Remote Insurance Data Analytics job openings in Idaho as of July 2026, with employment types broken down into 4% Internship, 79% Full Time, 13% Part Time, and 4% Contract. Highlights an 100% Remote job distribution.

Postdoctoral Fellow, NSF EPSCoR

University of Idaho Job

Moscow, ID • On-site, Remote

$60K/yr

Full-time

Posted 29 days ago


Job description

Position Information
Internal Posting? Posting Number SP005318P Position Title Postdoctoral Fellow, NSF EPSCoR Division/College College of Agricultural & Life Sciences Department IWRRI Location Boise Posting Context Statement Position Overview
We are seeking a postdoctoral scholar to contribute to a sub-project of the NSF EPSCoR project - Idaho Community-Engaged Resilience for Energy-Water Systems (I-CREWS), which seeks to increase understanding of how physical infrastructure, data, governance, local knowledge, and community context shape resilience under meteorological, population, and technological change. The postdoc will lead data analysis and modeling on the sub-project titled "Coupled Water and Energy Consequences of Agricultural-to-Urban Transitions in the Treasure Valley".

The postdoc will combine ground-based measurements of evapotranspiration (ET) in turfgrass and satellite-based consumptive use (CU) modeling to compare outdoor water use and associated energy demand across agricultural and urban land uses. The team will (1) develop and validate locally relevant methods to estimate consumptive use across mixed urban-agricultural landscapes, (2) estimate the energy required for water system operations under different land-use and infrastructure configurations, and (3) co-produce case studies with local partners to inform alternative futures modeling and resilience planning for the Treasure Valley.
Unit URL
https://iwrri.uidaho.edu/
Position Qualifications
Required Experience
  • Experience working with quantitative analysis, modeling, or data-driven methods related to energy-water systems
  • Experience collaborating with multidisciplinary teams, community partners, or stakeholder groups
  • Experience presenting or documenting research methods, findings, or technical information
  • Experience working with environmental or geospatial datasets, including remote sensing, flux tower or micrometeorological data, weather or climate data, or hydrologic observations
  • Experience conducting quantitative data analysis related to hydrologic systems, including statistics, time-series analysis, geospatial analysis, or model calibration and validation
  • Experience using scientific programming or data-analysis languages such as Python, R, or MATLAB to process environmental datasets and implement models
  • Evidence of scholarly activity through peer-reviewed publications, conference presentations, or equivalent research outputs
Required Education
  • PhD in hydrology, civil or environmental engineering, water resources, geography, environmental science, agricultural engineering, remote sensing, or a closely related field, completed by the start date.
Required Other
  • None
Additional Preferred
  • None
Physical Requirements & Working Conditions
  • None
Degree Requirement Listed degree qualification is required at time of hire
Posting Information
FLSA Status Exempt Employee Category Exempt Pay Range $60,000 annually or higher depending on experience Type of Appointment Fiscal Year FTE
1
Full Time/Part Time Full Time Funding This position is contingent upon the continuation of work and/or funding. A visa sponsorship is available for the position listed in this vacancy. Uncertain Posting Date 06/15/2026 Closing Date Open Until Filled Yes Special Instructions to Applicants
Applications received by July 10, 2026, will receive first consideration.
Applicant Resources https://www.uidaho.edu/human-resources/careers/applicant-resources Background Check Statement
Applicants who are selected as final possible candidates must be able to pass a criminal background check.
EEO Statement
The University of Idaho is an equal employment opportunity employer, including veterans and individuals with disabilities.