RESEARCH & EXPERIENCE
COVID-19 Research and Co-Authored Paper with the Indian Institute of Technology Delhi
While working with IIT Delhi, I conducted research on the statistical and mathematical modeling of the efficacy of various Non-Pharmaceutical Interventions in preventing the spread of COVID-19. I was also able to investigate other data science methods used to analyze COVID-19, including mathematical modeling, AI and ML, and scientific technology. I eventually co-authored a paper published in an international, peer-reviewed journal. READ MORE BELOW!
Research Analyst Intern at Scalar Gauge Fund, L.P. (Hedge Fund)
Scalar Gauge Fund, L.P. is a multi-strategy hedge fund based in Dallas, Texas that manages over $125 million in client investments. As an intern, I researched and analyzed a cross-border eCommerce company that had recently gone public. After interpreting financial statements, conducting market and competitor research, and creating a SWOT analysis, I presented my Investment Thesis to a committee of hedge fund managers. READ MORE BELOW!
COVID-19 RESEARCH WITH THE INDIAN INSTITUTE OF TECHNOLOGY DELHI
With in-person gatherings shutting down at the beginning of quarantine, the pandemic brought a tumultuous time for many. As I helplessly witnessed the world around me drastically change, I knew I didn't want to just stand by and watch; instead, I sought a way to actually contribute to the ending of the pandemic. As an intern with the Indian Institute of Technology Delhi, I found my place -- not only would I gain research experience and hard skills, but I would actually be able to approach a global problem and help find solutions.
My internship with IIT was the first real exposure I had to conducting academic research. I was able to work with Professor Anurag Rathore and post-doctoral students in statistical modeling of COVID-19. Specifically, the goal was to determine the most effective restrictions in preventing the spread of the disease in order to inform future public policy. I first used Microsoft Excel to gather data on cases and deaths, clean the data, manipulate the data to create 7 Day Moving Averages, and create hundreds of graphs to reveal possible trends. I also compiled information on different Non-Pharmaceutical Interventions (NPIs) such as lockdown length, presence of mask mandate, and travel restrictions for future use. We then used various multivariate analysis techniques to model the efficacy of different NPIs on the spread of COVID-19. Some of the analysis techniques we used included Principal Component Analysis, Partial Least Squares Regression, and Residence Time Distribution. I was able to see how computer science was utilized in real-world situations, as our statistical analysis required the use of software such as JMP and MATLAB, where coding was used. Our research was thorough and extensive, as the efficacy of NPIs was modeled on both a global scale (comparing restrictions across countries) and within the US (comparing restrictions across states). By researching and learning more about the data analysis techniques we used, I was able to understand how modeling techniques differed in assumptions and method, as well as the various components of data analysis. I was also able to see the process of academic research and how it is conducted. Currently, a paper I co-authored on this modeling is in the process of being published.
In addition to statistical modeling, a second area where I also contributed significantly was analyzing other broader methods of modeling COVID-19, including mathematical modeling, AI and ML, and scientific technology. I read through and grouped hundreds of articles based on content, and wrote analyses comparing studies based on considerations, assumptions, and techniques. Another paper I co-authored was written and published in an international, peer-reviewed journal. The link to the article is available below! Finally, I was also able to gain soft skills in communication and leadership. In order to work as a cross-border, multi-functional team, coordinating efforts required clear and concise communication. I also took initiative and went above and beyond my responsibilities, as I provided new perspectives and did extra research on factors that could affect data analysis. Overall, my experience as a research intern was amazing, and I am proud to say that I am now a published author. I learned a ton about data analysis and how conclusions are actually made, and I hope to pursue undergraduate research in the future!
RESEARCH ANALYST INTERN AT SCALAR GAUGE FUND, L.P. (HEDGE FUND)
My first exposure to economics came through debate while researching economic policy implications. Intrigued by the field, I eventually became interested in finance and sought to learn about various career options in a professional context. In Summer 2021, I interned at a hedge fund based in Dallas, where I eagerly learned from the experiences I gained.
As an intern with Scalar Gauge Fund, my primary task centered around analyzing a cross-border eCommerce company that had gone public just a month before. I enjoyed conducting in-depth research, putting pieces of the puzzle together as I uncovered the numbers behind the company. More specifically, essential aspects of my job included interpreting financial statements, analyzing sell-side research reports, conducting market and competitor research, and creating a proprietary SWOT analysis and Investment Memo. At the culmination of my internship, I eventually presented my research on the company to several hedge fund managers and answered detailed questions afterward.
Altogether, I found my experience in the financial industry riveting, and I especially enjoyed developing and applying my quantitative and analytical skills in the process. As I began the research process, I first consolidated important information from the company's prospectus and annual reports (10Ks and 10Qs). While studying the Income Statement, Balance Sheet, and Cash Flow Statement, I evaluated the company's growth, strength, and performance. Next, by reading through sell-side reports from Goldman Sachs, Raymond James, and KeyBanc, I gained a primitive understanding of the company's position in the market. Through further competitor and market research, I created charts on client distributions, graphs on growth trends, and a database of industry and competitor contacts. The aspect of data-driven decision-making is something I found particularly useful, and I hope to pursue data science further. Finally, consolidating all my research, I created an investment presentation with a Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analysis to deliver to the team. The presentation is available at this link. My strong public speaking and communication skills allowed me to present my findings effectively, and my colleagues were impressed with the level of work I had accomplished.
I was able to discover an abundance of career opportunities through multiple avenues. My analysis allowed me to discover how the company had integrated technology and business principles to develop and scale its solution effectively. Seeing the unique skillset that this combination offers has motivated me to pursue both computer science and business in college, with the possibility of completing an MBA beyond my undergraduate studies. Additionally, I have gained an understanding of finance careers through my firsthand experience in a professional business environment, and I intend to pursue a career in business. Possible areas of interest to me include social entrepreneurship, management consulting, and finance. I hope to explore all these career options at college while integrating social impact and technology to truly fulfill my ambitions!