What are your current job responsibilities?
I manage and report on the results of the financial models that serve to stress test Capital One‚ liquidity, and capital structure in the face of adverse economic conditions. This includes providing financial forecasts using time series forecasting with business context to senior leadership, and providing our results to the Federal Reserve as it is part of their annual CCAR process (Comprehensive Capital Analysis and Review) as mandated by the Dodd-Frank act.
Why did you choose to major in Economics?
I studied economics because I was, and still am, endlessly fascinated by the complex relationships, inputs, and effects that drive how we live.
What advice do have for current students who want to make the most out or their experience at UK Department of Economics?
Do not be afraid to step out of your comfort zone and challenge yourself. You are always capable of more than you think. Make connections with your professors and teaching assistants, and choose mentors. Make study groups - the people you study with may well be life long friends, and future professional connections.
How did your education in the Department of Economics prepare you for what you are doing today?
Understanding key economic inputs and drivers is a large part of success in my role. I use economic information from the federal reserve economic database on a weekly basis. Familiarity with the impacts that changes in the various drivers have on each other, on consumers, and on businesses provides the context that I need to report to people like my directors, and CFO.
What is your greatest professional accomplishment?
I am currently leading an internal initiative within my department to allow ourselves to become more technically savvy. As the predominance of data science creeps into more and more fields, learning to code in common languages and interface with cloud platforms like Amazon Web Services and Azure is becoming highly valuable for many professions outside of pure computer science / software development. As such, with my background working as a data scientist and in finance, I am teaching peers and leadership in my department how to convert models ran in excel, to models ran in Python for greater efficiency, automation capabilities, and ease of refinement.
What advice would you give current students or recent graduates interested in pursuing a career in your professional field? Recommend any data skills, programs, etc?
My advice would be to embrace statistics. Some form of statistical analysis has come up in every position I have had, and literacy in statistics in crucial to providing value and context to your results. Additionally, working knowledge of statistics is absolutely vital to any work in data science, as virtually all data science is grounded in statistical methods. R and Python are robust tools and easily accessible to learn for free.