The University of Chicago Masters Program in Computer Science students push boundaries and innovate across many facets of industry. Whether it’s developing seamless UX interfaces, engineering software at Fortune 500 companies, working in big data or keeping networks secure, our students use their applied-skills education from the MPCS to problem-solve, create, and elevate the computer science field. Learn from their stories and discover how a CS background can prepare you for cutting-edge careers and leadership roles.
Ryan Lempka (MSCS ‘19) is a Data Science Consultant at Accenture. He tells us what he likes most about data science, where he sees it revolutionizing the future, and why attending the MPCS part-time was the perfect fit for him.
What does a great day at work look like for you?
A great day involves presenting synthesized results of data analyses to my clients that deliver true business value. Or white boarding with a team of talented business/analytics experts to better understand my clients’ problems, and then working through solutions in code.
What do you enjoy most about data science?
Being able to constantly learn and approximate the future state of the world are the most enjoyable parts of data science for me.
Which programming language/technical skills do you use most often at work?
Python and R are the most common programming languages I use. For ETL work I have used both SQL and Alteryx. In terms of platforms it depends on the client, but one common platform we use to manage the machine learning life cycle is MLFlow on Azure Databricks.
Describe a data science problem at work that your MPCS knowledge helped you solve.
Recently I had to stitch together disparate data sources from a client to map certain elements of the company to a world map. I relied on skills I gained in my machine learning course at the University of Chicago, using pandas and NumPy to complete the exercise.
Did you come to the MPCS with a computer science background? What motivated you to apply and enroll?
No, my background was in IT and before that I was actually an actor. I decided I wanted to take my curiosity of computers to the next level, and I wanted to be someone who could use a computer to the fullest degree possible. IT gave me a high-level view of how computer systems worked, but I desired to understand how CPUs truly worked and the mathematics behind efficient algorithms.
What about the future of the data science/tech industry most excites you?
I feel that data science will fundamentally shift the efficiency of humanity (just as electricity and the internet did). I am most excited to see how data science can help in the realm of personalized medicine. The complexities of healthcare and the volume of available research continue to increase and I think AI/ML has the potential to reduce the cognitive load placed on physicians, allowing for more tailored and effective treatment plans for patients.
Please tell us about attending MPCS as a part-time student.
Attending the MPCS program as a part-time student required me to carefully manage my time but it was definitely feasible. Getting feedback from advisers/classmates on my class schedule was important for effectively budgeting my time, since time commitments outside of class varied from course to course. I decided to attend as a part-time student so that I could maintain my income while also getting a world-class education. For me, going part-time was a perfect fit and gave me the structure I needed to take my skills to the next level.
Would you recommend the MPCS to others?
Yes, definitely. The MPCS will train you to do more than just code. You will learn how to think like a computer scientist and this will echo in all areas of your professional and personal life. Moreover, whatever programming language you need to learn in the future will be primarily about learning syntax as the object-oriented fundamentals you get at through the MPCS will apply to all of the most common languages.
What is your favorite memory from your time as an MPCS student?
My favorite memory at the MPCS is a study session I had with my classmates the day before our advanced analytics midterm. It was great to work through concepts with my classmates and clarify some of the more difficult elements of the material. We all ended up getting sandwiches and eating them in Ryerson as we continued to white board problems for hours. Collaborating with my classmates really put me at ease before the exam and made me focus on the joy of problem solving and less about the stress of testing.
What was your favorite MPCS course?
Machine Learning. This course did a great job teaching me the nuts and bolts of machine learning. So often we use techniques like cross validation or models such as decision trees, without really understanding what is going on under the hood. The fact that all of these techniques and models are available in libraries such as sklearn and pandas means a lot of the technical detail is abstracted away. In the machine learning course we actually got to code everything from scratch and build these models and techniques from the ground up. Going through the exercises and exams really took me from being able to use the tools, to being able to understand how the tools actually worked.
How has your MPCS education helped you achieve your professional goals?
The MPCS has provided the technical skills to make me marketable for jobs in the most advanced technical fields. I was able to land a job as a data scientist after graduating and had other opportunities to work as a machine learning engineer and even a product manager.
What is a piece of advice you’d give someone considering applying to MPCS?
Be ready to work. The workload is high and the courses are very serious. I urge everyone who thinks that the program is a good fit for them to definitely apply, but also to prepare to adjust their schedules to account for the additional workload (especially if going part-time). Also, don't be afraid to take classes that are outside of your comfort zone, some of the most rewarding classes I took were ones that initially intimidated me.
Do you have any career advice for someone who's pursuing a job in your current field?
Do whatever you can to get hands on experience and find other people who are interested in data science to collaborate with and learn from. If possible, do side projects that involve data science and read as many books as you can on the subject.