Quantitative Analysis Unit Student Honors Intern at U.S. Securities and Exchange Commission
I interned with the Quantitative Analysis Unit (QAU) within the U.S. Securities and Exchange Commission (SEC) in New York City.
• I wrote a data input-output and cleaning program for trading blotters submitted for Exchange Traded Funds (ETF) to streamline the SEC’s process of formatting and aggregating these data and help identify non-compliance with regulation or even fraud.
• ETF-trading analysis had previously taken SEC analysts many hours of work and upwards of 1,000 lines of code per exam just to read in the irregularly formatted data. Using my program, ETFs can now be read in and analyzed in a fraction of that time and typically without the need for additional code.
• My supervisors gave me freedom to design the program, which I used to create an efficient and well documented program.
• I took a leadership role in directing the project and assigning tasks to the other intern.
I learned a lot interning with the QAU.
• In the week before the internship, I taught myself Python, which I used daily at the QAU.
• During the first week of the internship, I taught myself Q and KDB+, which I used to read through previously written SEC code for ETF-trading analysis.
• While reading through SEC code and creating my own program, I learned a lot about trading, creation, and redemption of ETFs.
• I participated in weekly lectures on machine learning given by one of my supervisors, a Ph.D. in statistics.
• I gained experience managing a GitLab repository with at least one other active user.