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# Summer Data Engineering & Research Associate - Space Analytics Project (Stealth)

- **Company:** Junwon Company
- **Location:** Northbrook, IL, United States
- **Salary:** $31,200.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Data Analysis, Big Data, Spreadsheets, Network Analysis, Information Engineering, Web Scraping, Data Visualization, Information Sciences, Python (Programming Language), Knowledge-Based Systems, SQL Databases, Technical Data Management Systems, Scripting, Information Technology, Api Design
- **Published:** June 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f3a0cbd2b20bf711

## About the Role

Do you have experience in Research?, * Computer Science

 * Data Science
 * Aerospace Engineering
 * Physics
 * Information Science
 * or related analytical/quantitative fields, * Experience with Python, R, or similar scripting languages
 * Strong attention to detail
 * Excellent research instincts
 * Comfort with independent work
 * Familiarity with spreadsheets and structured data

Strong pluses:

 * SQL/database experience
 * Web scraping or API experience
 * Data visualization, UX/UI
 * Graph/network analysis
 * Familiarity with AI tooling/workflows
 * Interest in aerospace, science, or complex systems

## Description

We're seeking a motivated undergraduate or graduate student for a flexible summer role supporting an early-stage stealth project focused on space travel, human networks, and large-scale data analysis.

This is a unique opportunity to work directly with a founder on an unconventional research and analytics initiative at the intersection of:

 * data engineering
 * research infrastructure
 * AI-assisted knowledge systems
 * network analysis
 * public records
 * and human space travel

The role involves helping build structured datasets and analytical tooling within the space ecosystem.

This is an ideal opportunity for someone who enjoys:

 * turning messy information into usable systems,
 * writing scripts and automations,
 * uncovering patterns in complex historical/technical data,
 * visualizing information for an audience
 * and working on intellectually ambitious problems.


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