Samuel Okoye grew up working in the family business. His parents owned a factory that peels and processes cassavas into various food products. Samuel noticed the machines would fail at regular intervals, forcing the factory to suspend production and call in a technician to fix it.
He started keeping a log to record each failure incident, and as he collected more and more data he began to wonder if it was possible to use some sort of mathematical equation to predict machine failure and intervene before it was too late.
“After a couple of years, I told my dad, ‘If we have this number of customers and this kind of load on the machine, we can predict when the machine is going to break so we can have an engineer onsite before it happens.” He said, ‘No, it doesn’t work that way. The machine just breaks because it wants to break,’” Samuel recalled.
Back then, maintenance management software wasn’t as mainstream as it is now, but Samuel was onto something.
He decided to study mechanical engineering so he would understand machines better and perhaps, along the way, find a way to predict when a machine would fail. However, machine failure is determined by predictive models that use historical data to forecast future events. After spending several years working as a mechanical engineer, Samuel decided to study data science so he could understand machines better. Less than a month after completing the Data Science Career Track at Springboard, Samuel landed a role as an IT consultant at Kforce, working with a client called Health Equity, a healthcare company that helps people set up a health savings account (HSA) so they can make health insurance payments from their paycheck and maintain their HSA even if they switch employers.
Before I decided to go into data science, I did a lot of projects which were heavily based on mechanical engineering. I usually collect data in the process, but because I wasn’t a data scientist, I didn’t appreciate how much information data could contain. Moving into data science helped me see value in things other engineers don’t really care about. If I were to go back and do an engineering project, I would get more out of it because I would be making a decision not only based on materials, but data as well.
Mechanical engineering is my domain. I like it, but it gets boring over time because you’re pretty much doing the same thing over and over.
So when I was researching different career paths, I discovered that data science is growing all the time and it’s very current. Engineering is current as well, but if a design engineer uses AutoCAD to do design, that’s pretty much what they’re going to be doing [for the rest of their career].
Before I started at Springboard, my goals weren't that well defined. I was just trying to see if I could improve my skills and see where it takes me, but the more I learn about data science, the more I actually love it. So now I consider it a career switch.
I’m working for a health insurance company in a data science role that is based heavily on SQL. One of my first projects is to migrate data from an old database into a new one. But in that process, we have to do some data analysis, clean the data, and so on. They hired me as a support engineer.
Anything to do with predictions gets me excited. In a typical mechanical engineering project, we don't start doing something unless we’ve defined a problem statement. Then we follow a process and make sure the final product matches the problem statement. Compare that with any prediction problem in data science, where you don’t know what’s going to happen in the process. We don’t know if the model is going to be accurate, or what the data might reveal. Those are the kinds of problems I like solving.
I’ve always wanted to work for the aerospace engineering company Lockheed Martin. I wanted to work for them so badly but the fact that I don’t have my US citizenship yet has hindered me a lot because these roles require a security clearance. I’m interested in anything that has to do with aerospace engineering or consumer products.
When I was doing the research to determine my new career path, I considered getting a master’s degree in computer science, probability, or statistics. But then I stumbled into data analytics, data science, and machine learning. I started reading about it and it was mind-blowing for me.
I had recently met someone at a coffee shop who completed a bootcamp and became a developer, and she suggested I do the same. So I started comparing bootcamps versus a master’s degree. I found that if you want to learn the skills to be successful in the market, a bootcamp is a faster option because you can solve more real-life problems. When I read the reviews from former Springboard students, I thought, “Man, this is really good.”
The mentorship program at Springboard was great. In the beginning, I thought having a mentor meant having a tutor, so I wasn’t sure how to treat the relationship. But once I started to understand it better, I became more independent. When it was time for me to do job interviews and complete assessments, I knew how to find answers on my own.
As for the career coaches, they were on another level. I think Springboard did a good job of hiring coaches with different personalities. I met every single career coach and then I picked the one that matched my vibe. Those guys will push you instead of beating around the bush or trying not to hurt your feelings, and I like honesty.
My most enjoyable moment was when I hit the 50% mark because after that it felt like another chapter of my life was starting. All of the projects after that became so much easier, and that was because I followed everything by the book.
The moment I was able to complete projects without doing a lot of Google searches or consulting my notes, I started feeling more confident when I went on job interviews. There was this feeling like, "I’m a data scientist now. I can do this.”
I’ve spoken to at least three people about that, and a buddy of mine actually just started a course at Springboard. When I shared my experience, he actually went ahead and enrolled that same day.
My advice is: you need mentorship. These people are working in the industry already and they are a huge resource. If you are someone who really wants a change, Springboard is the right place for you. I got a job less than a month after I finished Springboard in August. By August 24, I got my first offer with JP Morgan. Two days later, I got an interview with Intel, and two weeks later, they offered me a job, which came kind of late, because I had already accepted the job at Health Equity.