Data Analyst, Youth Policy Lab, University of Michigan

How to Apply

A cover letter and resume are required for consideration for this position. The cover letter should be included in the same document as your resume and should specifically address your interest in this position and highlight related skills and experience.

The Ford School is committed to providing a positive and inclusive work environment. This includes providing employees with flexible work opportunities. This position follows a hybrid schedule and will generally be expected to be in the office 3-4 days/week. 

Summary

The Youth Policy Lab is looking for a Data Analyst to become an active member of the Lab. As a data analyst, you will provide analytic support to several research projects and report to the Data Team Manager. Data analysts also work very closely with University of Michigan faculty, including Lab co-directors Brian and Robin Jacob.

The University of Michigan Youth Policy Lab, a joint research center between the Ford School and the Institute for Social Research, helps community and government agencies make better decisions by evaluating and strengthening programs intended to address some of our most pressing social challenges. Using rigorous evaluation design and data analysis, we work closely with partners to build a future where public investments are based on strong evidence, so all Michiganders have a pathway to prosperity. For more information, please visit us at www.youthpolicylab.umich.edu.  

This position may be filled at the intermediate level, with a salary range of $60,000 to $68,000, depending on the candidate's qualifications and experience. 

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
• Paid parental leave 

Responsibilities*

Data Cleaning and Preparation (50%)

• Perform data cleaning and merging procedures on and prepare data sets for different statistical analyses
• Work collaboratively with project managers and Principal Investigators (PIs) to understand project goals, data requirements, and objectives; answer questions about the structure and nature of datasets
• Communicate proactively with project managers and PIs about data progress, timelines, and issues
• Identify and resolve time-sensitive data issues
• Implement data storage and retrieval solutions for efficient access by members of the research team

Data Analysis (25%)

• Conduct data analysis and prepare results for memos, spreadsheets (can perform complex functions), and presentations targeting both policymaker and academic audiences. Perform quality checks
• Prepare and document final versions of complex datasets including cleaning, recoding, reformatting, and outputting data in a variety of formats as necessary for different audiences

Code and Documentation Development (15%)

• Develop and improve processes for extracting, transforming, and loading various data sources into analytic datasets
• Build, maintain, and update scripts/programs aimed at improving data cleaning processes at YPL by writing automation scripts and templates
• Develop data documentation (codebooks, technical appendices, etc.) that includes key information for processing and analysis
• Identify opportunities to improve the efficiency and quality of data processing and analysis, and collaborate with team members to implement solutions

Data Visualization (10%)

• Develop data visualizations to effectively communicate data in reports and dashboards
• If the position is filled at the intermediate level, you will also support research design, determining and interpreting research results, and independently writing up results of analyses.  

Required Qualifications*

For associate-level: Bachelor's degree in a relevant field (public policy, economics, public administration, etc) with coursework in statistical analysis and some experience using Stata (preferred), R, SAS, or similar programming languages.

• Extensive experience working with Stata, R, SAS, or similar programming languages may be considered in lieu of a degree.

For intermediate-level: Graduate-level degree in a relevant field (public policy, economics, public administration, etc) with substantial coursework in statistical analysis and extensive experience using Stata (preferred), R, SAS, or similar programming languages

• 2+ years of relevant professional experience

Documented foundation in applied econometrics or statistics, including multiple regression (experience or related coursework minimally at the BA level)

Commitment to principles of social justice, equity, diversity, and inclusion. For more information on the University's commitment to these principles, please visit: https://diversity.umich.edu/ 

Underfill Statement

This position may be underfilled at a lower classification depending on the qualifications of the selected candidate.