How to apply for Data Analyst, Air Quality Life Index

About University of Chicago, Energy Policy Institute

The Energy Policy Institute at the University of Chicago produces energy and environmental research to inform energy choices. The Air Quality Life Index (AQLI) is one of its flagship projects, translating satellite data into clear impacts on life expectancy. Working here means your data work feeds directly into public reports and an open-access platform.

About the role

You will run the annual AQLI data pipeline, turning raw satellite data into usable formats and applying the calculations behind the index. You will maintain the GitHub repository, generate figures for the annual report, and work with external website developers on the AQLI platform. The role is remote in India and full-time.

A typical day

A typical day may involve writing or debugging pipeline code to process raw satellite data, updating the GitHub repository, and producing figures for the annual report. You may also meet with external website developers to coordinate updates to the AQLI platform. Exact routines are not stated in the posting, so ask about team structure and daily workflow in the interview.

Who University of Chicago, Energy Policy Institute is looking for

• Has hands-on experience processing satellite or large geospatial datasets into analysis-ready formats
• Can build and run a repeatable data pipeline from raw inputs to final figures
• Manages a GitHub repository with clean version control and clear documentation
• Communicates well with external partners, including website developers, and can turn analysis into report-ready visuals

Tips for this application

• Show a concrete example of a data pipeline you built or ran, including the raw data source, the processing steps, and the final output.
• Link your GitHub profile and point to a repository where you maintain code, not just one-off scripts.
• If you have worked with satellite or geospatial data, name the datasets and tools (for example, specific satellite products, Python, or GIS libraries).
• Include a sample figure or report visual you generated, and explain what calculation produced it.
• Mention any experience coordinating with non-technical partners such as web developers or external teams, since the role lists this explicitly.

What to cover in your cover letter

Describe a data pipeline you implemented end to end, from raw satellite or large data to usable output. Explain how you manage a GitHub repository for a recurring analysis. Give an example of a figure you built for a report and the calculation behind it. Note any experience liaising with external partners such as website developers.

Research before applying

• Read the AQLI methodology and recent annual report on the EPIC website to understand how the index is calculated.
• Look at the AQLI open-access GitHub repository to see the current code, data formats, and pipeline structure.
• Review EPIC's other research areas to understand how AQLI fits into the institute's broader work.
• Check the AQLI platform and its published figures to see what outputs the role supports.

Likely interview topics

Based on the job description, expect questions about:

• Walk through the steps you would take to process raw satellite data into a usable format for the AQLI.
• How do you structure a GitHub repository so an annual pipeline can be rerun and updated by others?
• Describe a time you generated figures for a report. What tools did you use and how did you check accuracy?
• How would you handle a discrepancy between your analysis and what an external website developer has published?
• What is your experience with satellite data specifically, and which datasets or tools have you used?

Common mistakes to avoid

• Listing data analysis skills without showing any pipeline or repository work you actually built.
• Ignoring the satellite data requirement and treating this as a general analyst role.
• Applying without looking at the AQLI methodology or the public GitHub repository, which the role directly involves.