Research Analyst (Data Science)

Job Information

Job Summary:

The University of Chicago Poverty Lab is seeking a Research Analyst with strong research, methodological, and programming skills to support social policy research projects. The Research Analyst will have the opportunity to apply tools and approaches from methodologies in both modern data science and traditional econometrics to original projects impacting homelessness, college access and completion, and workforce development. The Research Analyst will contribute to a growing practice of developing advanced analytical solutions to provide data-driven technical assistance to governmental and non-profit partners.

The successful candidate will have experience in applying a variety of statistical modeling and machine learning approaches to large datasets in real-world settings. From project inception to delivery, the Research Analyst will contribute to all facets of data collection processing, model development, and implementation. This position requires an individual who is able to work as a part of small research teams running multiple projects concurrently. The position offers the opportunity to work directly with leading social policy researchers at the University of Chicago and local city agency staff, as well as a team of Urban Labs research staff and student research assistants.

Responsibilities:

Working with partners to identify analytical approaches to solve specific research questions
Construct, train and deploy scalable machine learning algorithms for a variety of research projects
Preparing results of models for memos, spreadsheets, and presentations targeting both policymakers and academic researchers
Build and interpret traditional econometric inferential models for experimental and non-experimental evaluations
Designing custom solutions for entity resolution and record linkage
Assisting in writing grant proposals, preparing IRB proposals, and obtaining other research permits
Other duties as assigned

Competencies:

Strong interest in social policy required
Prior experience or education in applying data science tools to real-world problems preferred
Strong background in applied statistics & modeling required
Strong written and verbal communication skills required
Ability to manage multiple projects simultaneously and meet tight deadlines required
Excellent organizational skills and attention to detail required
Ability to work both independently and as a team member required
Ability to work discretely with sensitive and confidential data required

Additional Requirements

Education, Experience, and Certifications:

Education:

Bachelor’s degree in economics, public policy, statistics or other relevant social/mathematical science field required
Coursework in statistics, econometrics, data science, bioinformatics or computer science required
Master’s degree preferred

Experience:

A minimum of two years of relevant experience required. Experience gained in school counts towards requirement
Experience working with large and complex datasets strongly preferred
Proficiency with one or more languages such as R, Python, or SAS required
Experience with relational databases a plus
Experience working on field experiments preferred
Experience applying machine learning algorithms in operational environments preferred

Required Documents: