Madeline Sherry ’24, Math Major and minor in Computer Science and Data Science, shares about their internship with Ubiq.ai – a mobility optimization company located in Vienna, Austria
“My name is Madeleine Sherry (class of 2024) and I’m a Math major expecting to minor in Data Science and Computer Science. I spent this summer working as a Data Science Intern for Ubiq.ai – a mobility optimization company located in Vienna, Austria. I pursued this internship during my study abroad experience in Vienna, where I was also taking an advanced German course and an internship seminar focused on business models and European cultural understanding.
I wasn’t sure what to expect initially, as this internship was my first exploration into the world of data science and analytics outside of the classroom, but I was pleasantly surprised by the work that I was assigned. Given real responsibilities that followed the goals of the company, I felt like I made a positive contribution by completing my tasks.
In order to analyze certain aspects of the data that I was working with, I was tasked with connecting Google BigQuery to a language like Python or R where more complex analytics and operations can be performed. Within BigQuery, SQL queries can be performed, which was what I initially looked into. Though these are useful in certain situations, the data cannot be exported with ease to be analyzed in these other languages. Creating a pipeline, so to speak, was the best option for getting all the data accurately represented in our analysis. I worked towards this goal during the first few weeks of my internship through lots of trial and error. Initially using R, the data transferred over with few problems but one crucial variable was mutated during the connection process which proved complex to maneuver. This led me to pursue the same process in Python, which proved to be successful as there were more avenues to connect to BigQuery. I had already created the data cleaning and analysis within R, so after connecting to Python I sent the file created to R where the second two steps were applied, and results could be exported to a Google Sheet.
With the support of the two data scientists that work at Ubiq and my supervisor, I was able to achieve the desired results and create a functioning pipeline that they can use in the future. This project helped me grow my skill set as a data scientist, as I had to problem solve and adapt. One of the other special things about my internship was the fact that Ubiq highly prioritizes learning amongst employees. Through workshops and “brown bags” as they call them, I was able to sit in on talks where highly skilled data scientists and engineers discussed their newfound discoveries and tricks. These allowed me to get a better understanding of the field and its applications, as most of the time the skills shown were for informational purposes rather than implementation at work.
Looking to the near future, I now have a better understanding of the field that I am hoping to enter after graduation. Through working and collaborating with the data scientists here, I was able to finally see how all of my learning in the classroom works in the “real world”. Going into my senior year, I am now able to look excitedly towards the classes I am planning to take and know what I need to focus on in order to succeed in the data science field if I choose to pursue that path.”