This career change came about during the pandemic of 2020 soon after I lost my job of four years in sales and customer service. I was having a difficult time find an opportunity that peaked my interest, so there came a point where I had to start thinking outside what I was used to. I came across this application, Career Karma, developed by a few men in the computer science industry, that wanted a platform to give back to the digital world of current and up-coming engineers and developers. It was completely free so I figured, “Why not try this out and see what happens?”. This platform introduced me to other free apps like Grasshopper, Mimo, Sololearn, and Codecademy. These apps helped me get a basic understanding of such things as Python, SQL, and HTML. Career Karma also paired me up with a mentor who had either recently gone through a bootcamp similar to Flatiron School or was graduating soon and they helped me understand different career paths (i.e. Software Engineering, UI/UX, Cyber Security, and Data Science). At first, I was leaning towards software engineering, but after having a few Zoom meetings with my mentor, she encouraged me to look further into data science due to my comfort with arithmetic. She advised me to focus on python mainly because this language is used primarily within data science and not to worry about anything else at the time. Advice I now understand, as if you’re someone just dipping their toes into the computer science pool, you may be overwhelmed with all the languages.
After a few weeks of periodically playing around with these learning apps, I had to start venturing out and seeing what school/bootcamp I could potentially get into. Career Karma advised me and many others on how to interview with these schools and what they are looking for within their prospective students. For the majority of these bootcamps/schools, they will lead a two step interview process. They first ask for a “behavioral interview” and then a “technical interview”. The behavioral interview is where you get to describe to them why you are considering this field of study and what you have done to prepare yourself to get to this point. The technical interview is where you display in real time what you have learned up to this point. I’ve learned that you don’t need to be fluent with these languages but need to have an understanding on fundamentals such as: lists, loops, and dictionaries. You will actually work within the platform, Anaconda, to showcase what you know. Specifically for the data science pathway, there is also a statistical/calculus concept they will ask you to describe. Don’t worry if you don’t know how to find the solution to the problem, that’s what the computer will be for down the road; but they want to know that you can understand what the equations are trying to solve. Utilize your interviewer like a teacher of your class you're taking to work through the problem if you aren’t confident with coming to a solution.
In summary, I chose to pursue a career within data science for a few reasons. I am always looking for a challenge, whether personally or professionally. I’m comfortable with mathematics and different concepts to find solutions to everyday questions leading to future understanding of real time numbers and how to create conclusive information about what’s happening right now. I am also looking for a better work/life balance than I had previously. From what I’ve seen within job postings, the tech industry really takes care of their employees. The benefits advertised in these postings sound too good to be true, but I guess in reality, if the employee is happy and feels taken care of, then they will likely have a stronger work ethic and want to perform well for the company and have a desire to continuously learn and grow with the industry. I am a kinetic learner and like to work within group settings. This type of work is always hands on and you and your peers will likely be working collaboratively within avenues such as GitHub. As a data scientist, your objective is to create real time analyses and summarize with recommendations for business stakeholders to effectively make educated decisions on how to move forward with their operations.
If you are considering getting into data science, I hope my initial journey and synopsis of it was useful and answered some of your questions. As I continue my endeavors on becoming a full fledge data scientist, I will be sharing my work and thoughts along the way on this site. Feel free to share with friends and family that you think would have an interest or you see doing well within this industry because it’s not going anywhere any time soon and becoming the next big booming industry of the world!