At the time of this interview, Alexander worked as a Data Scientist at Guidehouse. Now, Alexander works as a Senior Data Scientist for the US Government Accountability Office.

This interview is an excerpt of a longer conversation with alumni, who work and study data science.

Please tell us a little about yourself.

I graduated with an economics degree in 2018, taking some computer science classes along the way as an undergrad, since I was interested in broadening my quantitative skills.  After completing my undergraduate studies, I got my masters at the UVA Data Science Institute (DSI), which is now the School of Data Science.  I currently work as a consultant for Guidehouse and am responsible for leading several data analytics projects for a public sector client.  While at UVA, I was part of the Virginia Gentlemen and the Admissions Liaison for the DSI. 

What technical skills did you develop, and what skills can students develop, to go into your field?

In my opinion, the most important skill in data science is the ability to code.  I predominantly use Python in my day-to-day work.  Any students looking to become data scientists should try to take classes that give them a chance to develop programming skills; otherwise, they ought to try to develop these skills on their own.  If you are looking for self-paced learning, there are a number of online platforms that offer more structured coursework (e.g., Coursera), but you can supplement your learning with a combination of YouTube videos, data science blogs, etc.  Try to find what works best for you.  Even when looking for jobs that are less coding-intensive, understanding how to code something like a simple SQL query might give you an advantage in the job hunt.  For students looking to hone their coding abilities, Kaggle competitions are another great way to challenge yourself and grow your data science skill set.

What do you enjoy about your work?  What do you find challenging?  What did you find surprising?

Guidehouse has given me many chances to grow, not just in a technical sense.  Aside from my client work, I currently lead our AI and Automation Thought Leadership team, so I spend time learning and writing about state-of-the-art data science technologies and methodology.  I did not expect to be in a leadership position in a decently sized consulting firm right after school, but since Guidehouse is still a newer company, I have been afforded many opportunities that I might not have had elsewhere to help the firm grow.  On the challenging side, my client work often feels like a long game of telephone; I have to balance, keep track, and make sense of many stakeholders' interests, new information, and additional requirements, which frequently are indirectly relayed to me as I'm developing solutions.  It always feels good though, to make those ends meet, and to help people realize business value through high-impact data products, based on information that they've always had, but never closely examined; I enjoy this aspect of my job the most.