Work type



Capability Area

Information Technology

Graduate Research Assistant - Python/Django Developer

Apply now Job no: 495208 Work type: Intermittent Location: Chicago – Hyde Park, University of Chicago Campus, IL Capability Area: Application Development, Data Services


NORC at the University of Chicago is seeking passionate problem-solvers excited by new challenges who enjoy working on multiple projects in a fast-paced environment. In this position the Graduate Research Assistant (GRA) will be called upon to apply their computer science expertise and skills to create innovative solutions addressing key social issues such as early childhood education, criminal justice, economics, and labor. The GRA will be expected to quickly and independently pick up and apply new skills while working in a team environment.


NORC's Information Technology program provides technology services to our staff and clients. Given the critical role technology plays in our day-to-day lives, we are committed to providing professional, high-quality solutions in order to further our collective goal of advancing social science research.​

  • Working on a team with developers, engineers, researchers, and statisticians to develop new data-oriented technologies and software solutions for collecting and analyzing data
  • Working with web service APIs or developing novel web scraping programs to pull data from a variety of online sources
  • Manipulating, transforming, and analyzing large volumes of data
  • Maintaining, customizing, and enhancing existing systems
  • Facility in Python programming and web development using the Django framework in a Linux environment
  • Familiarity with web UI development using JavaScript, CSS, and HTML
  • Familiarity with PostgreSQL database technology
  • Strong written and verbal communication skills
  • Bachelor’s degree with a major in computer science, mathematics, statistics, analytic public policy or sociology, or related field
  • Development of production quality code for assembling, processing, and analyzing data from disparate sources to enable inferences of significance to the design or evaluation of policies or programs
  • Experience with front-end web technologies (e.g., jQuery, CSS/LESS, Vue.js, Jinja2) preferred
  • Experience working with various social media APIs (e.g., Twitter, Facebook) preferred
  • Data visualization tools/methods preferred
  • Interest in social science research preferred
  • Analytic skills involving topic modeling, natural language processing, and machine learning preferred

NORC at the University of Chicago is an objective, non-partisan research institution that delivers reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions. Since 1941, our teams have conducted groundbreaking studies, created and applied innovative methods and tools, and advanced principles of scientific integrity and collaboration. Today, government, corporate, and nonprofit clients around the world partner with us to transform increasingly complex information into useful knowledge.


For over 75 years, NORC has evolved in many ways, moving the needle with research methods, technical applications and groundbreaking research findings. But our tradition of excellence, passion for innovation, and commitment to collegiality have remained constant components of who we are as a brand, and who each of us is as a member of the NORC team. With world-class benefits, a business casual environment, and an emphasis on continuous learning, NORC is a place where people join for the stellar research and analysis work for which we’re known, and stay for the relationships they form with their colleagues who take pride in the impact their work is making on a global scale.


NORC is an affirmative action, equal opportunity employer that values and actively seeks diversity in the workforce. NORC evaluates qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, sexual orientation, gender identity, and other legally- protected characteristics.


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