Aspiring data scientists who are fresh out of school are often advised to seek their first job as a data analyst instead, given the hefty requirements for data science roles–typically a master’s degree and at least five years of experience working with data. However, just a few months after completing the Data Science Career Track at Springboard, Pizon Shetu landed a job as a data scientist at Whiterock AI, a New York-based company that builds software for commercial real estate data.
Pizon had majored in computer science in college but after graduating, found that he was ambivalent about embarking on a career as a software engineer. When he landed a role as an analyst doing basic Excel functions and data entry, that’s when he discovered his love for data and his passion for using graphical representations to explain the unexplainable. Soon after, he discovered Springboard and decided to pursue a career change to become a full-fledged data scientist.
While I was studying computer science at Queens College, I got a job working as an analyst at Sodexo/Centerplate [now Sodexo Live!]. I did a lot of data entry in Excel but it wasn’t anything serious and didn’t involve any coding. Shortly before graduation, I was still trying to decide if I really wanted a career as a software engineer. My classes consisted mostly of working on Leetcode problems and data structures and algorithms. It was a grind.
Then, towards the end of the semester, I took an ‘Intro to Machine Learning’ class and I was really interested in it. I started doing Kaggle projects in my spare time and I realized I was having fun with it. That’s when I took the step and joined Springboard.
I’m very fortunate. I had no experience in the data science field, and the job descriptions always say: “Required: Master's or PhD and 10 years of experience." So, I felt very blessed that I was able to land an opportunity as a data scientist.I was actually aiming for a data analyst role or a junior data science role, but I guess I was lucky.
We’re a real estate machine learning company and we analyze real estate data to make it digestible for everyday public use.
A big part of my job is carrying out the ETL process–extracting the data, cleaning the data, and learning from it. I look through our datasets and see, okay, what are we working with? What can we use for future models? What kinds of products are we trying to sell, and which datasets complement those products?
Even though I studied computer science, I lacked the experience of coding on a day-to-day basis. My classmates got internships at big companies like Lyft, Uber, Amazon, and Google, but I didn’t apply myself as much as I wanted to, to be completely honest. So I decided that a bootcamp would help me get up to speed and get the experience I needed.
When you’re in a bootcamp, you can learn the material at your own pace. In the work environment, deadlines matter. You can’t get extensions. Investors and upper management are counting on you to get work done on time. That’s something I struggled with in the beginning–having to work at the same speed as somebody who has five or six years of experience.
I’d heard really good things about Springboard. Two of my classmates at Queens College had participated in Springboard programs and they recommended it to me, so I thought, why not? Springboard also had a lot of good reviews, and I knew data science was a booming industry. Also, Springboard teaches you the entire data science process from end to end while letting you apply your knowledge through different projects. That’s what interested me the most.
If I'm being honest, I think I found a job in data science because of my capstone projects. My project was about real estate. The part I’m really proud of is the report I wrote, because not a lot of people think about that. Most people think, okay, you clean the data, you do some modeling, make some predictions, and you have your results. But how do you visualize and express that work so that the average person can understand it? That’s where the report comes in.
My employer looked at that report and said, "Wow. We're really impressed with how detail-oriented you were. You explained every metric and why you did what you did.”
My mentor’s name was Branko Kovac [data science specialist at Logikka]. He was very candid and honest. I had to take a lot of breaks due to personal reasons and family issues. He was very supportive but at the same time he kept me on track. Those little things really made an impact on my ability to finish the bootcamp. When I missed an assignment he would say, “Okay, what can we do to make it better?” That’s something I really appreciated.
My job search was full of anxiety and uncertainty.. But I will say this; another thing I really appreciated from Springboard was the resume review. I iterated my resume about 25-30 times, and each time it just got better and better. My career coach helped me out with my resume. She gave me guidelines on what hiring managers are looking for and how to structure my resume. For example, even though I had a background in computer science and math, I put that at the bottom of my resume, but then I learned that hiring managers look for candidates with those degrees.
Do your research before you jump into anything. Find people who are working in that field and get their feedback. Also, YouTube is a great resource. There’s so much information out there. But bear in mind that sometimes YouTube content creators only highlight the positives, so look out for that, too. Then, test the waters and see if you’ll like the work. If you’re going for data science, try out a few easy Kaggle projects. If you’re ready to make that career change, find the right curriculum, like Springboard, that can really help you get there.