Research Area Specialist Sr

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How to Apply

A cover letter is required and should be attached as the first page of your resume. The letter should address your specific interest in the position, and outline your experience that directly relates to the position.

Summary

The Panel Study of Income Dynamics (PSID) is a social science study that has collected economic, social, and demographic data from U.S. adults since 1968. The PSID project is located within the Survey Research Center (SRC) at the Institute for Social Research (ISR). Our central mission is to provide the scientific research community of economists, sociologists, demographers, and other social scientists with accurate data and documentation.  PSID includes major supplemental data collections such as the Child Development Supplement (CDS) and the Transition into Adulthood Supplement (TAS). The project is looking for multiple Research Associates to join the Data Processing team who are experienced in the domains of data cleaning and processing, data management, creation of codebooks and user guides, and report writing.

Why Work at Michigan?

Why Work at Michigan?

In addition to a career filled with purpose and opportunity, the University of Michigan offers a comprehensive benefits package to help you stay well, protect yourself and your family, and plan for a secure future. Benefits include:

  • Generous time off
  • A retirement plan that provides two-for-one matching contributions with immediate vesting
  • Many choices for comprehensive health insurance
  • Life insurance
  • Long-term disability coverage
  • Flexible spending accounts for healthcare and dependent care expenses

The Institute for Social Research at the University of Michigan seeks to employ a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan, to maintain the excellence of the university, and to ground our research in varied disciplines, perspectives, and ways of knowing and learning.

 Learn more about U-M benefits.

Responsibilities*

What You’ll Do

Intermediate:

  • With supervision and following training by a senior member of the Data Processing Team, assist with the processing of raw data obtained from the computer assisted interview application
  • Use SAS to clean, process, and transform social science panel data to prepare for editing; write and revise SAS programs to transform raw data; determine the correct number of records and merge on correct person identifiers to raw data; produce SAS output for identifying potential problems with record integrity; application of best practice rules for data management including identifying and flagging problems with primary keys and primary-foreign key relationships
  • Conduct data consistency and data quality checks
  • Apply complex longitudinal rules to perform family composition and economic data editing
  • Code open-ended answers from survey questions
  • Construct detailed codebook documentation that creates variable-level specifications and code frames in an Oracle Forms application; create variable names, labels, and formats; construct new and maintain existing cross year index that categorizes survey measures and maps comparable measures across interviews; develop documentation of data files, including web-based codebooks and other electronic documentation
  • Write and edit technical reports and training materials, including processing and editing in Word, creation of charts, graphs, and tables in Excel
  • Assist the project in other areas, including data analysis, writing tutorials to instruct users about how to create and analyze data, assisting with user help, and compiling information about protocols and instruments used in other similar studies

Senior:

  • As a senior member of the Data Processing team, lead the data processing effort on PSID major supplemental studies from start to finish, including specification of data to ensure the correct collection of the data; manipulating the raw survey data and paradata; creating final result codes; generating complex variables and scales; reviewing and evaluating results
  • Prepare analysis files from complex longitudinal data and paradata, conduct data consistency and data quality checks, and conduct statistical analysis for substantive and quality assessments
  • Supervise and train staff in the processing and editing of supplemental study data
  • Provide technical expertise and training to other members of the Data Processing team on processing and analysis. Assist team members with understanding their tasks, reviewing their work, resolving their questions and any problems they encounter
  • Assist the project in other areas as needed, which may include but is not limited to testing and troubleshooting the questionnaire application and data center merges prior to public release. During production, conduct analysis of the data as they are collected, including data quality checks for internal use as needed.Present project information and results at meetings and conferences as needed. Provide statistical support for sponsor progress reports and as needed for Project Investigators and external scientists.

Required Qualifications*

We’d like to hear from you if you have:

  • Intermediate: Bachelor’s degree; Senior: Master’s degree in social science, statistics, or related field.
  • 4 or more (5+ Senior) years of experience with management and analysis of social science survey data
  • Experience using SAS or other statistical programming languages (Stata, SPSS, R) to manage and manipulate data with an emphasis on data step programming and merging data
  • Demonstrated competency in statistics, including producing and assessing descriptive statistics, evaluating outliers, and handling missing data
  • Demonstrated ability to subset, merge, and restructure complex data files
  • Experience in identifying and solving data problems and applying complex sample design features and rules
  • Ability to work successfully in a team environment, excellent interpersonal skills, and excellent verbal and written communication skills
  • Self-directed, organized, and highly attentive to detail

Desired Qualifications*

We are especially interested if you also have:

  • Proficient in SAS, with an emphasis on advanced programming, data step programming and using macro statements
  • Master’s degree in economics, sociology, survey methods, or related field
  • Experience in the processing and editing of longitudinal social science survey data 
  • Intermediate knowledge of statistics and experience producing balanced panel output, weighted frequencies, means, scatterplots, and manipulating raw data collected at various levels.

Work Locations

These positions will be on-site at the University of Michigan Offices in Ann Arbor, with flexible scheduling and remote opportunities made available within our overall center policies.

Underfill Statement

Openings may be filled at the Research Area Specialist Senior or Research Area Specialist Intermediate level and salaries will correspond to the appropriate classification based on education and experiences:

Research Area Specialist Senior: $75K-85K

Research Area Specialist Intermediate: $60K-$75K

Additional Information

The statements included in this description are intended to reflect the general nature and level of work assigned to this classification and should not be interpreted as all-inclusive.

The Institute for Social Research (ISR) at the University of Michigan seeks to recruit and retain a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan, to maintain the excellence of the university, and to ground our research in varied disciplines, perspectives, and ways of knowing and learning. For more about ISR’s commitment to Diversity, Equity and Inclusion, please click here.

Institute for Social Research job openings are posted for a minimum of fourteen (14) calendar days. This opening may be removed from posting boards and filled any time after the minimum posting period has ended. 

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.