The Insurance Institute for Highway Safety (IIHS) is an independent, nonprofit scientific and educational organization dedicated to reducing the losses — deaths, injuries and property damage — from motor vehicle crashes.

The Highway Loss Data Institute (HLDI) shares and supports this mission through scientific studies of insurance data representing the human and economic losses resulting from the ownership and operation of different types of vehicles and by publishing insurance loss results by vehicle make and model.

Both organizations are wholly supported by auto insurers and insurance associations.

Compensation consists of a competitive salary and a 403(b) retirement plan with employer contributions. Other benefits include health insurance (with dental and vision coverage), life insurance, medical and dependent care flex spending accounts and three weeks of paid vacation in your first year.

IIHS-HLDI participates in E-Verify.

Research Analyst

The Highway Loss Data Institute (HLDI) seeks an experienced Research Analyst to join our research team in Arlington, VA.

The Research Analyst will lead research projects that rely on statistical techniques to analyze vast amounts of insurance data. Previous HLDI studies include some of the first evaluations of collision avoidance technologies, evaluations of the effect of marijuana legalization on insurance claim frequency and analyses of the effectiveness of antilock braking systems on motorcycles.

Primary Duties

  • Identify highway safety and/or insurance issues to research, formulate research questions and produce project plans
  • Analyze records of over 400 million vehicles to quantify the benefits of lifesaving and cost-reducing technologies and to explain how insurance costs vary from vehicle to vehicle
  • Produce published reports and serve as a primary resource on alternative analytical procedures
  • Present findings to technical and nontechnical audiences including high-level executives
  • Represent HLDI and IIHS to insurance companies and at meetings of roadway safety professionals


  • Graduate degree in a quantitative field such as statistics, mathematics, machine learning, etc., with prior applicable experience preferred
  • Advanced analytical skills and demonstrated knowledge of statistical distributions and modeling techniques
  • Experience with databases and record sets with millions of records
  • Proficiency with statistical modeling tools and one or more programming languages (SAS and SQL skills strongly preferred)
  • Attention to detail and problem-solving abilities are essential
  • Capable of working independently with minimal supervision and as part of a team
  • Excellent written and verbal communication skills
  • An interest in highway safety and automobiles

To apply, email your resume and salary requirements to

Engineering Technician

The Insurance Institute for Highway Safety (IIHS) seeks an Engineering Technician to join our crash avoidance team in Ruckersville, VA. 

The Engineer Technician will work with other members of the crash avoidance team to ensure that all tests are properly prepared and conducted on schedule. Tests include official vehicle rating evaluations for front crash prevention and headlights, as well as research tests to develop new rating programs.

Primary Duties

  • Conducts or assists with all pre- and post-test procedures
  • Ensures test set-up, execution and reporting meticulously follow established procedures
  • Applies crash avoidance test protocols to plan and execute crash avoidance tests
  • Ensures all data collection is error-free
  • Assists in testing to support research projects and development of new protocols
  • Provides support for other IIHS projects as needed


  • Associate degree in an engineering field (preferred) or three years of relevant experience
  • Must have a valid driver’s license
  • Able to work/drive at night
  • Must be able to stand for extended periods, crawl under and around vehicles and lift equipment (up to 50 pounds).

To apply, email your resume and salary requirements to