How my AI background at Warrington translated into a data science career
The Master of Science in Information Systems and Operations Management program not only provides the tools needed to break into data science, but challenges students with real world projects to apply those tools. My experience in the program taught me to focus on solving problems, and that was the differentiator for me during the interview process on my way to a career as a Data Scientist at Guidehouse LLP.
Most programs or bootcamps promise to teach you Python and SQL in 4 weeks, but employers seek more than an entry-level understanding of programming languages. Python and SQL are simply tools used to solve problems. Employers look for candidates who have built solutions to solve problems they would encounter in the industry. Coming out of the MS-ISOM program at Warrington, my solutions were what separated me from other applicants.
During my first year, I learned Excel, Python, SQL, and machine learning fundamentals. But during the summer, I took the practicum course with Dr. Jim Hoover, and that’s where I learned how to truly apply the tools I had already acquired to derive insight and business value. My specific Accenture-sponsored project was a broad prompt to analyze sentiment regarding federal agencies. I learned how to give structure to ambiguity by defining the details of the project. My team and I decided which agencies to research and what problems to pinpoint. Using a topic model, polarity, subjectivity, and time series analysis, I built a solution, then came back with areas of improvement for these agencies.
Employers need candidates who can gather requirements, navigate through ambiguity, and follow through with a solution. When it comes to the interview, anyone can say they “know” Python, but I was able to say I developed a solution from start to finish, using real world “dirty” data and making evidence-based recommendations for change.
These are the most important skills I use in my role as a Data Science Consultant every day. Clients may not always understand the issue, but I must bring organization from that chaos. I must build solutions with the help of my team and domain experts. Above all, my solutions need to be explainable while driving impact for the client, otherwise the fanciest solution can be rendered useless.
Typically, everyone who wants to get into data science asks, “What tools do I need to learn?” The ISOM program taught me to ask, “What solutions can I build in my industry?”
