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On-site
Austin, Texas
Posted · 20.09.2026
Greenhouse (US)

# (SPRING) Data Scientist Intern - PhD

Integra FEC - Internships

Integra is hiring entrepreneurial and quantitatively-skilled students/graduates with data analytics experience who are interested in translating their academic interests into the real-world applications  to identify, investigate and analyze fraud in various domains, including finance, healthcare and cryptocurrencies. Integra is a boutique economic consulting and forensic analytics firm that has worked with government agencies and private entities to analyze many complex and high-profile schemes. Our team applies data science and econometric techniques and intensely values each employee to take initiative and to be curious while operating as a data detective to solve complex problems. Our main office is also conveniently located adjacent to the UT Austin campus which enables us to closely interface with the academic environment and the university’s top intellectual talent.   As an intern you will code software used to automate processes, scrape and collect large data sets, and perform advanced econometric analysis. You will have flexibility in the programming language used, but scripting languages such as R, Python, and SQL are used most often. The internship is also designed to give you:   Exposure to how technical degrees such as economics, statistics, finance, engineering, computer science, and physics are used in industry   Opportunities to work on team-based and individual projects   Visibility to industry experts   Job Qualifications:   Familiarity with R, SQL, Python, or other scripting languages Proficiency in Microsoft Excel Attention to detail with big-picture understanding Ability to work well in teams Highest ethical standards Must be enrolled in a PhD program Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.  

This job was verified from Greenhouse (US). Applications are completed on the original source.

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