Research Specialist
University of Illinois at Springfield - Springfield, IL

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The person in this position conducts research activity on behalf of the Illinois Department of Transportation (IDOT), Division of Traffic Safety. The ideal candidate will be someone who possesses very strong research and data manipulation skills. The person must develop and link statewide crash data to health care data using advanced probabilistic methods and several descriptive and multivariate statistical techniques, including multiple regression, logistic regression and structural equation modeling. The linked data will be used to analyze and study financial and medical outcomes of individuals who are involved in motor vehicle crashes. The position will be funded by IDOT and the person will work closely with IDOT staff.

  • Import crash and health related databases and link individual level records that are devoid of identifiers using a set of indirect linkage variables. To do the linkage, learn and utilize a specific federally provided data linkage MS Access software program known as “CODES2000”.
  • Clean and transform data fields as needed prior to data analysis. Make needed transformations of the raw data fields based on a thorough knowledge of state and local agency policy and practices. Transformations must also be made with an understanding of the data requirements of more advanced statistical modeling.
  • Conduct detailed and highly complex multivariate statistical analyses of the linked datasets. Process large datasets using SAS software, impute missing links and missing values, and produce analytical SAS output for further interpretation, discussion and reporting. Interpreting the output requires knowledge of both advanced statistical methods and theories as well as intimate knowledge of the features of SAS software.
  • Prepare analytical reports for use by IDOT and others related to policy issues such as helmet usage by motorcyclists and the impact of such usage on health and health care costs. Explain results of complex statistical analyses using narrative that can be understood by a generalist audience.

Required Qualifications:
  • B.A. or B.S. in Math, Statistics, Computer Science, or Social Sciences, with a very strong quantitative research emphasis.
  • Five years quantitative research experience.
  • Strong communication, problem-solving and decision-making capabilities and the ability to work with minimal direction.
  • Experience working with large statewide or nationwide databases using SAS and other statistical packages, SQL and Microsoft Access, as well as experience in the management of large datasets on multiple hardware processing platforms.
  • A thorough knowledge of and prior experience with SAS.
  • Working knowledge of Microsoft Access, Excel and Word.
  • A thorough knowledge of probability theory and statistics; Bayesian Modeling; structural equation modeling; identification and selection of exogenous and endogenous variables; and, a thorough grasp of techniques needed to maximize the goodness of fit of the models.
  • Ability to write reports of sufficient quality to be published in refereed journals.

Preferred Qualifications:
Master’s Degree or Ph.D.
Knowledge of IDOT traffic safety policies and procedures.

Compensation and Benefits: Benefits include 24 days vacation leave, 25 days sick leave, nine state holidays, two floating holidays, and a choice of health and retirement plans. An H-1B visa is required for any non-U.S. citizen to be eligible for the full range of benefits. Salary commensurate with experience and qualifications.

For consideration, select the “Apply to Job” button below , create or update your profile, and submit a cover letter explaining your interest and qualifications relative to this position; a resume; and, names and contact information (phone and email address) for three current professional references. Screening of applications will begin Nov. 12, 2012 and the search will continue until the position is filled. The anticipated start date is January 1, 2013. If selected for an interview, applicants must submit an official transcript at the time of the interview.

Pre-employment background screening will be required of the selected candidate.

UIS is an affirmative action/equal opportunity employer with a strong institutional commitment to recruitment and retention of a diverse and inclusive campus community. Persons with disabilities, women and minorities are encouraged to apply.

University of Illinois at Springfield - 19 months ago - save job - block
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