How I structured my Activity and Time to become a Data Scientist
Strategize your busy times to achieve the data dream
As data enthusiasts, we are all trying to learn all the data science material as fast as possible to achieve the data scientist position. You then realize that time might not be on your side because you might be professionally juggling many work assignments, a student finishing the thesis, or an aspirant with many job applications to send.
I have been in that position before, finding the right time to learn data science amidst my future uncertainty after education and looking for a job. I did not instantly become a Data Scientist when I graduated. Instead, I build up myself for the employment I want.
In this article, I want to share how I broke my time to become a Data Scientist at each stage of my life.
Never doubt that you could become a Data Scientist; it takes much preparation and chances you carve by yourself.
Activity and Time Structure as a Student
My passion for data showed up as a master's student in Biology. Whether it is the right choice or not for my future I did not know at that time. I know that this field is piqued my interest, and I certainly want to know more about Data Science.
Although, just like any other student out there. We have many lessons to attend, many homework to turn in, and much thesis research to analyze. In my case, this is what I did:
At least twice a week at night, when I did not have much study workload, I would research Data Science and what I needed to become a Data Scientist.
When I have my lesson and homework, I will try to relate them to Data Science. e. g. I have homework to review biology journals; then, I would use a Data Science approach to do my homework by looking at the data.
My university has a programming lesson (In-class and out-class). I would take both of these lessons to hone my programming skills. To refine it, I would take an online programming course for at least an hour or two at the weekend.
I will create a portfolio of my thesis research as a Data Science research project when I have my thesis. This is because I analyzed data, a valid Data Science project.
Juggling Data Science passion and life as a student is not easy, and what is more challenging is that there are no guidelines on how we could become a Data Science when your major is not what modern data science expects you to be.
After you graduate, it is even more complex—many of my classmates and friends are going for a PhD or into employment. It is a different case; I was rejected by both the PhD program and employment, whether it was for a Data Science job or not.
I have a lot of doubt in myself, and I am almost not following up to become a Data Scientist. Although what I did next when I was unemployed is the key to becoming the Data Science I am right now.
Activity and Time Structure as an Unemployment
This is the time when uncertainty creeps in, and you would doubt everything you have learned. I did not have a lot of confidence at that time and always thinking; “Is Data Science the way?”, “Am I doing the right thing?” “What if I only keep burdening my parent?” and so on.
Amidst that, I keep holding on to that “Data Dream”, where I strategize my time and activity in my unemployment time to upgrade my knowledge. This is what I did and structured to become the Data Scientist during my unemployment time:
At least three times a week, I would go to a calm place to study Data Science online courses and read the upcoming data science article. My go-to place is the library close to my apartment, but quiet and distraction-free is good.
Every day I would look at the online job board to know what the company wants and adjust my skill set to what the company wants in Data Scientist. At first, I focused on the Biology specific company, but I broadened my search as the requirement was too high over time. Whether I apply for the job is different, but I know what the company looks for.
I am periodically trying to solve data science problems, whether on Kaggle or just the existing training dataset. I set a target that I could “solve” the problem that might arise in the real world each month—for example, fraud detection or credit scoring.
I am attending Offline Data Science Bootcamp. I would proudly say that I am a Data Scientist that is previously attending the Bootcamp. What differentiates me from the other student is that I already prepare before joining this Bootcamp. I am joining the Bootcamp to accelerate my programming skill, not my Data Science skill. I believe my student time and previous employment time have given me that experience.
I was offered the job of Data Science trainer at the Bootcamp I attended previously.
Isn’t Data Science Trainer working as a Data Scientist? Yes and No; I would say yes because I learned a lot on-site what an ideal Data Scientist should be, and no, because the job did not necessarily do what Data Scientist does in the real world.
This is why I am preparing myself even more for my non-” Data Science” employment to become Data Scientist.
Activity and Time Structure as an Employed Person
This section would benefit both those employed in the job function that is close to the data field and those who are not.
I am employed as a Data Science Trainer, but I still want to pave my way into the proper Data Scientist I want. The time-constrained are even more real during employment as I have an immense responsibility and limited time for myself (My previous workplace work-life balance was not good).
That is why I need to be more creative in strategizing my activity to become a Data Scientist. This is what I did to achieve that:
I am applying Data Science in any project within my work. I am teaching Data Science, but it doesn’t mean I cannot use what I teach in my job; for example, I scourge the course data to find the best way to create the teaching curriculum.
I am enhancing my connection with people. In my line of work, I met many kinds of people from many lines of work. In this case, I try to establish a good relationship with everybody. Whether it would be helpful to get the data job or not is essential; what is important is that every connection you find will prove helpful in some time. Although, in my case, it would be.
At least three times a week, I would try learning a new Data Science concept. This keeps my head refreshed as the Data Science field is constantly evolving. Even in my current employment, I still use this tactic as I need a different approach to solving business problems.
Once a month, I would create a new Data Science portfolio and update my CV. I do this if any employment I want is open, and I did not miss the chance to become a Data Scientist.
I am creating the connection you never had before by attending the seminar, conference, or joining the club. Life is full of random occurrences; just like the normal distribution, even if the chances something happens are close to the mean, it doesn’t mean that the outlier would never happen. My preparation to become a Data Scientist is becoming fruitful because of the connection I made in a place I had never thought of. I got the Data Scientist job by a referral from another Data Scientist in the same organization as me (spoiler: It is not a Data-related organization).
I did this to prepare myself for the Data Science job. It takes a lot of preparation and many twists, but preparing yourself in a good position would undoubtedly improve your chance of becoming a Data Scientist.
Never doubt that you could become a Data Scientist; it takes much preparation and chances you carve by yourself. Strategize your activity and time, and you will undoubtedly achieve that data dream.
Conclusion
Achieving the Data Dream is not easy for some people; getting a Data Scientist job would require a lot of preparation and determination. It would be best if you believed you could get the job and set yourself up the best way possible. Strategize your activity and time in each stage of your life, and you might become a Data Scientist.