What is Data Science
Data science is the process of receiving, understanding, analyzing, visualizing, and modeling data. It begins with a problem, a question, and data that claims to have the answer. The data is often unorganized and must be sorted through to get the information that’s needed. It must then be analyzed and understood to deduce if the issue in question can be solved with it. In order to see the data clearly and draw conclusions, a visualization is created. Once the process is completed, a solution can be derived from the now clear and concise information.
Why did I decide to become a Data Scientist
For one, I like that Data Science is a large field with a wide variety of jobs, and within those jobs, you are always learning. It is important for me to have the option of remote work, as work/life balance is of necessity to me, and a career in data science can provide a remote work life unlike many other careers. I have family members in the tech industry, both are software engineers, and they enjoy their work immensely, which motivates me greatly. But most importantly, I enjoy the process of discovering something, beginning to research it, learning new things constantly and being intellectually stimulated all the while. I'm always helping people solve problems and I really enjoy the process even though it can be difficult, for in the end it's very rewarding. Learning Data Science gives me the tools to find better and more efficient solutions to problems at work and in my life. Even more importantly, it speeds up the analytics process exponentially, which could be an invaluable asset in time restricted situations.
Background
My experience with inefficiency in jobs and what I know is possible to achieve with data science showed me the stark contrast between workplaces with automation and those without. I became aware of the need for automation in my first job in tech doing data entry, this pushed me to start actively looking for and exploring data and automation. On my phone, I started making shortcuts in the shortcuts app which is basically puzzle coding. I really enjoyed it but it bothered me that certain things weren't possible. Well, the only way to achieve anything is to go to the fundamentals, to the roots, or to do the actual coding. So that's what I did. I found I enjoy problem solving more than the actual development which pointed me in the direction of data science.
Another thing that pointed me towards data science is my interest in Linguistics. I learn languages, primarily writing systems. I spent time studying Devanagari, Cyrillic, Arabic, Hebrew, Greek, and Thai and I noticed patterns and themes in and between languages. Knowing how to somewhat read these languages makes it possible for me to learn and be aware of information or data that I otherwise would not have been able to understand. That is quite amazing to me, and data science can be viewed in a similar way. With Data Science tools, you possess the skills to retrieve understandable solutions from a multitude and otherwise intelligible data.
One area of Data Science I'm interested to learn more about is recommendation systems. One system that really improves my everyday life is the Spotify recommendation system. I listen to music constantly and I’ve watched the songs that Spotify recommends to me become more and more accurate and nuanced as time goes on. This really inspires me to become a data scientist because it's so applicable and relevant in my life and so many others.
Why I chose Flatiron School
I chose to go to Flatiron School rather than do self study primarily for the collaboration and in person feedback, as well as the structured time to get work done. A challenge I face is the academics, because it is an immersive bootcamp, the pace is accelerated and I'm still finding my feet, only being in the first week of the 15 week program. I know that I am growing and learning with each passing day and that's what I'm aiming for, so it's a win.
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