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(FALL) Data Scientist Intern - PhD

integra Austin, Texas

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  • open for 115 days (90+ without a fill is a strong ghost signal)
  • no salary disclosed (correlates with ghost postings)

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About the role

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.

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