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MSDS Alumni Profile: Wyatt Scott
Wyatt D. Scott
Employment
S&P Global Ratings, Senior Quantitative Analyst (Charlottesville, VA)
Education
M.S. in Data Science 2024, University of Virginia
B.A. in Government, Law, and National Security, Misericordia University
Wyatt D. Scott is a Senior Quantitative Analyst at S&P Global Ratings in Charlottesville, Virginia. With a background in government, law, and national security, Wyatt credits the University of Virginia’s M.S. in Data Science program for equipping him with the technical skills and hands-on experience needed to pivot into a more quantitative and programming-focused role.
From mastering R and Python to collaborating on impactful group projects, Wyatt reflects on the transformative impact of the program on his career and shares his aspirations for the future, including possible plans to pursue a Ph.D. at UVA.
Q: Walk us through what you did at work today.
To start the day, I read through and responded to emails; then, I pivoted to look over the Azure DevOps “Boards” for the projects I’m involved in. Once I knew what to tackle for the day, I jumped into RStudio, reviewed my notes on where I left off the day before, and then spent most of the day programming. Specifically, I worked on building an R6 Class to encapsulate the logic for a certain pipeline. I then spent some time testing the class and using it in a Shiny app I am building. I also had a few meetings to check in with teammates, discuss priorities, and demo some of the code I’ve been working on.
Q: What did you learn in the M.S. in Data Science (MSDS) program that you have found most useful in your career so far? And what do you wish you had learned?
Most of everything I learned throughout the MSDS program has proven useful in my career thus far. Granted, I entered the program with limited programming and modeling experience. If I had to choose a few ‘most useful’ things I learned throughout the program, one would be EVERYTHING we covered in DS6001 Practice and Application of Data Science, and then dynamic programming, object-oriented programming, and all things version control. What tied it all together in ways I use every day was DS5111 Data Engineering.
In terms of what I wish I had learned — the ability to jump into someone else’s code base and hit the ground running is table stakes in the professional world, so more exposure on that front would have been helpful. Another is more general programming management — we learned to write neat (or tidy) code — but some more foundational training on project management specific to small-to-medium-sized code projects would be great.
Q: How did the MSDS Capstone project prepare you for your current work?
The Capstone project I was on was transformative: getting hands-on training and experience coding in a team using Git and working with Databricks and Azure DevOps.
Q: Were there specific classes, projects, or professors that you found particularly influential in preparing you for your career?
I’ve touched on some of the classes that were particularly influential in preparing me for my career, but all the professors I worked with were awesome. A few shoutouts, though, go to Program Director and Professor Jon Kropko, Professor Olivares, Yuri Malitsky, and Sodiq Adewole. The courses focused on fundamentals (DS5100 Programming for Data Science, STAT6021 Linear Models for Data Science, and CS5012 Foundations of Computer Science) were most influential for my programming abilities.
Q: What networking opportunities or alumni resources played a role in securing your current position or aiding your professional development?
I worked with my current employer before and during my time in the MSDS program, but the role I was in before my current one was mainly qualitative, though I found fun ways to leverage what I was learning during the program to automate some of our repetitive workflow tasks, which helped me when interviewing for roles, including my current one.
The program creates spaces and opportunities for students to network, so I encourage prospective or current students to get involved or tune in to anything they can. Having a close-knit cohort to bounce ideas off of, speak to about career trajectories, and encourage one another along the way played a big role in getting me through the program and into my current role.
Q: How do you perceive the impact of your MSDS degree on your career advancement and opportunities?
I made a somewhat significant pivot in my career, albeit remaining with the same employer, and without the MSDS degree, that either would not have happened, or I would have ended up on some circuitous route to doing so. The MSDS degree has an immense impact on my career and future opportunities. It’s a great alumni network, too. You get out of it as much as you put in, though the faculty and staff are accommodating and delightful to work with.
Q: Was there a student experience or classmate/cohort interaction during your time at School of Data Science that stands out as particularly memorable or transformative for you?
The group projects were transformative throughout the degree — in many great ways, though some not so great. In either case, the group work taught me a lot about working on data science projects collaboratively, and I made some great friends along the way.
Q: As you look ahead, where do you envision yourself professionally in the next 5-10 years? Are there specific career goals, projects, or milestones you aspire to achieve in the coming years?
In the next few years, I’d like to settle into my current role and hone my R and Python programming capabilities, perhaps to the point where I don’t have to pull up the help documentation each time I call `pd.melt` or `purr::pmap`. I’m currently working on an internal data utilities package, so I’d like to build out really useful functions therein with thorough unit tests and useful, understandable documentation.
In the next five to ten years, I’d like to return to the School of Data Science for my Ph.D.!
