Pre-Doctoral Research Fellow For
Dr. John M. Griffin
This position is a unique opportunity to work alongside financial experts in conducting original finance and economic research. The position involves responsibilities that serve as excellent preparation for Ph.D. programs in finance or economics, including data processing and analysis, model design, simulation techniques, literature reviews, and presentations. The research fellows will work closely with Dr. John Griffin (and his co-authors) on research projects in forensic finance, blockchain and cryptocurrency, structured finance, or healthcare. Dr. Griffin is seeking applicants who are dedicated to rigorous research and motivated to study fraud. Research fellows are welcome to request recommendation letters from the financial experts with whom they work.
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Professor John M. Griffin is the James A. Elkins Centennial Chair in Finance at McCombs School of Business, University of Texas at Austin, and CEO of Integra FEC. Dr. Griffin is a leading forensic finance expert, specializing in understanding the role of potentially illegal, illicit, or immoral actions in financial markets. His research has analyzed potential fraud related to cryptocurrencies, PPP fraud, CMBS, CLOs, the 2007-2008 financial crisis, bonds and structured finance products, credit ratings, derivatives, insider trading, market manipulation, investment bank disclosures, financial market anomalies and hedge funds. His papers have won top finance awards and, according to the SEC, he is the second most cited academic in recent SEC rulemaking. He has published over 30 papers in the top finance and economics journals and is widely cited. His recent research has been profiled in Bloomberg, The Wall Street Journal, The New York Times, and over 750 other news outlets around the world.
LOCATION
Austin, TX
EMPLOYMENT TYPE
Full-time
Job Description
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Conducting research to develop and investigate hypotheses in forensic finance. Topics may include cryptocurrencies, derivatives, or other complex financial instruments.
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Data extraction and processing: writing scripts to retrieve and organize data
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Data analysis: analyzing large datasets to find insights and fraudulent patterns, by thoughtfully applying the appropriate tools and algorithms
Qualifications
Required
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Completion of bachelor's degree in statistics, mathematics, engineering, computer science, data science, economics, or other quantitative field
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Intellectual curiosity and interest in fraud analysis
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Attention to detail
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Highest ethical standards
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Strong teamwork abilities
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Excellent grades
Preferred
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Prior research experience, either for independent research or as research assistant
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Excellent skills in R, Python, and/or SQL
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Potential interest in pursuing a Ph.D. in Finance, Statistics, Economics, or other quantitative field in the future. ​