Financial Data Analyst at NISA Investment Advisors, LLC
Bachelor’s degree in Mathematics with minors in Actuarial Science and Economics in 2018
I chose to be a math major because I knew that I had strong quantitative and logic skills, but I wasn’t very interested in the lab work that came along with Physics or Chemistry. My older sister (an economist at the time) advised me to take and economics course or two while in college, and I decided that the applied mathematics of economics and business was appealing to me. After taking CS180 as a requirement for the math major, I realized that computer science skills were going to be crucial to studying business/economics data, so I decided to pursue data science and statistics courses. The blend of all of these allowed me to have a very diverse skill set for entering the job market directly out of undergrad (which I had planned to do from early in my career at Truman).
I currently hold a position as a financial data analyst at NISA Investment Advisors, LLC in St. Louis, MO (Clayton). In this role, I work with the Portfolio Management Solutions team to deliver automated market data reports, trade processing tools, and database structures/maintenance for end users that are fixed income and derivatives traders and their supporting analysts.
How I use math in my job:
Most of the math I use in my day to day work is logic that runs database queries and automated processing engines. Organizing a workflow of processes so that the processing can complete in an organized and efficient manor while sending and receiving data from various sources is quite common. Additionally, I use a lot of financial mathematics calculations (such as present value and it’s extensions), in developing reports identifying relative value between fixed income securities as well as identifying trade opportunities based on portfolio holdings and exposures.
Advice for students getting ready to hit the job market or apply to graduate school:
My advice for anyone interested in pursuing a career in data science or quantitative finance/business is to spend some time developing coding skills. In particular, database skills such as using SQL to read and manipulate data are crucial to everyday business, and are transferable to many different applications. Additionally, learn the basics of a statistical software like R or Python to get an idea of what sorts of analysis are possible using these platforms. Tableau is another software for data visualization that many businesses/labs are using, providing another outlet for learning transferable skills. And finally, don’t sign up for your first job, just because it will pay you the most. Instead, look for the company that has the most extensive training program/development opportunities. I have learned a lot of new, transferable skills in the first two years of my job, and my management group is extremely supportive of me taking work time to research a new tool, or hone my computing or business-specific skills. I’m sure this experience will give me a lot to talk about in any future interviews I may have, and definitely prepare me for a successful career going forward.