Open Positions

Urban Research Corps

The below position(s) are currently available in the Urban Research Corps. Please submit your materials via the Google Form linked below.

Research Engineer

Deadline to apply: October 4, 2021

The Mansueto Institute is conducting a project focused on the analysis of social and economic outcomes in American households using data science methods. The project will involve analyzing survey results on a monthly basis that track household experiences across a range of topics including housing security, spending habits, and health patterns. The role will involve maintaining a Python-based pipeline, deploying it on a cloud platform, and creating visualizations.

The role is up to 15 hours per week starting Fall Quarter through Winter 2022, with the possibility to extend.

Required Qualifications:

  • Fluency in Python and/or R..
  • Seeking a graduate degree (e.g., Master’s or PhD).
  • Experience developing pipelines that involve data ingestion, standardization, and transformation.
  • Experience with structured, semi-structured, and/or unstructured data formats (e.g., CSV, JSON, Simple Feature, raster/GeoTIFF, and/or XML).
  • Knowledge of software development practices, such as: version control; package management / virtual environments (e.g., pyenv, poetry, PipEnv, conda, Docker); unit testing; code review.
  • Experience with Linux-based systems and command line tools such as Bash.
  • Eagerness to constantly learn, ask questions, share knowledge, and teach others.
  • Empathetic and self-aware mindset; express mutual respect, trust, and willingness to assist team members.
  • Ability to work in a dynamic environment where requirements and solutions evolve through collaboration.
  • Ability to articulate technical barriers and proactively solicit help from team members.
  • Ability to work independently on the design and development of research methods.
  • Ability to scope the feasibility of unstructured research tasks; self-delegate and create personalized work plans; identify, evaluate, and apply existing solutions to avoid “reinventing-the-wheel.”
  • Capable of autodidactic learning from academic articles, self-guided tutorials, Stack Overflow, and package documentation.

Preferred Qualifications:

  • A Bachelor’s degree in a technical subject area is not required, but some formal training in math, computer science, statistics, economics, physics, engineering, or social science is strongly preferred.
  • Significant experience in Python, R, and SQL.
  • Experience with ETL and data ingestion through web scrapes, S3/FTP sync, and/or APIs.
  • Experience with visualization tools (e.g., matplotlib, ggplot2, Mapbox, Javascript visualization libraries).
  • Experience writing clean and readable documentation for code repositories and datasets.
  • Experience working in the tech industry, applied research organizations, as part of a cross-functional software development team, or working with a principal investigator.
  • Familiarity with PyTorch, TensorFlow, Keras, TensorFlow Probability, and/or PyMC3. Practical understanding of probability and statistics, including Bayesian inference.
  • Familiarity with workflow management platforms such as Apache Airflow, dbt (data build tool), or large-scale batch and streaming processing frameworks like Apache Beam or Google Cloud Dataflow.
  • Familiarity with Google Cloud Platform, Amazon Web Services, Microsoft Azure, Midway HPC / SLURM.
  • Familiarity with cloud deployment frameworks (e.g., Docker, Google Cloud Deployment Manager, AWS CloudFormation, Azure Resource Manager, Serverless Framework, TerraForm, Heroku).
  • Familiarity with JavaScript, HTML/HTML5, CSS and/or JSON.

Class Level Eligibility:

All current graduate students.

How to Apply

Participants must complete a short online questionnaire, submit their resume, and provide a link to a previous project that includes a code sample. The interview process involves a 30-minute conversation and a short take-home technical assessment.

To apply, please submit the following materials:

  • Google Form Q&A
  • PDF Resume
  • Example of previous project work that includes code


For questions, please email or visit the URC FAQ Page.