From Chemical Engineering to Data Science
Hello everyone! My name is Leonie and I am a Chemical Engineering graduate and I am a Data Analyst in a start-up company.
You may, wonder — how can you become a Data Analyst?
Well, here’s my story.
How I began to know about Data Science?
It began in the end of year 2019, where I just graduated from college. It feels like my weight have been lift out a little bit lol.
As a fresh graduate, I am determined to find a job. I even landed my first and second interview for a job before I even graduated.
But, that’s it.
Not long after that, the pandemic broke around March of 2020. It‘s really devastating for me. Not only I have to deal with quarter life crisis, but I also become more stressed because of the pandemic.
The time keeps tickling and I never realize that it’s already been 8 months since I graduate and staying at home all the time kinda make me stressed.
Dozens of job application I have sent but there’s no answer. My family tried to cheer me up, they say that everyone is having a hard time in this pandemic, but still, I can’t just sit all day long.
There is a moment of time that I thought “Maybe I am not suited in this Chemical Engineering industry.”
I figure out that I have to explore my potential. So, I began to learn a lot of things. I learn about Digital Marketing, Graphic Design, and starting a new business (although I already have one since my college year).
Then, at one time, my friend suggests me to learn how to ‘code’. He even suggested that he will help me learn it. Since I’m open to all kind of new knowledge, I accept his offer. I learn how to code almost every day (but only for like an hour or so).
After that, we kinda lost contact and I didn’t continue my lesson. When we talk again, I told him that I am learning marketing now and he once again suggest me to find out about Data Science.
After learning about data science, I am amazed at how interesting it is. It took a long time to make this decision, but I make a decision to learn data science and drop other things that I have done (including letting go of my dreams to become a Process Engineer, which is a really really hard thing to do, I won’t lie but I cry like almost every day before I make this decision).
and from that time, on September of 2020, I started my Data Science Journey.
How I started my Data Science Journey
In my first journey, I notice that it is really important to set up your goals, and your goals have to be SMART (Specific, Measurable, Achievable, Relevant and Time bound). At that time, my goals is to land a job related to Data Science on March of 2021 (which I succeed to do so!).
It is really tricky to learn something, moreover if you’re on this journey alone. I think the most important thing is to be Realistic. So, I set a goal to learn data science in 6 months and I made a planner/tracker to track my progress every day. Basically, it looks like this.
So basically, for the first 1–3 months, I learn how to code with Python in the morning and learn Data Science in the afternoon from Mon-Fri. I usually practice my coding skills in leetcode and I learn basic Data Science skills.
If you ask me, did I learn it in an online course? No, no I don’t (although I did join a Tableau online course in coursera, which is worth it!). I learn all of it in youtube :)
So what I did is I will search for a data science syllabus in an online courses, a bachelor, or a master degree (you will find this a lot in the internet) and I will look at all of them and basicly summarize them together (example : if I found one subjects in all 3 of them, I will take it as I thought it is important!).
After listing out all the syllabus, I will set out a goal each week for 6 months (to see if 6 months is an ideal time for me to learn all of those subjects). What I also learn is you have to be flexible and have a second and third plan. For example : If I made a plan to learn about subject A but in reality I need more time to learn about it, I will add the following weeks to learn subject A before moving on to the next subject.
It is important to learn all of it properly! Rather than knowing a lot of things but only in the surface, I think it’s much more important to know only like 1–2 things but you already master it.
Note : I actually learn straight into data science with python in jupyter notebook before starting to learn statistics (because I already learn some of it in college) but I recommend you guys to learn it side by side!
After about 4 months, I started to made some Data Science portfolio. So, my day goes like this :
- Monday : Practice SQL skills in the morning, Learn Data Science in the afternoon.
- Tuesday : Practice SQL skills in the morning, Learn Data Science in the afternoon + search dataset for portfolio ( I usually find it in Kaggle), do some EDA(Exploratory Data Analysis).
- Wednesday : Practice SQL skills in the morning, start to do Data Cleaning and if possible, answer some questions from EDA.
- Thursday : Continue to answer the questions from EDA, if I have time I usually do this while making my portfolio.
- Friday : Read-proof and tidying up my portfolio that I will share on my Github or my website.
- Saturday : Free Time (lol yes, I need a break)
- Sunday : Free Time, but I usually already planned out the material that I have to learn for the following weeks.
How I landed my first job as a Data Analyst
After having about 6 portfolios, I started to braved up myself to apply to some job. Thankfully, I got a lot of replies. Usually when you apply for a Data Analyst position, you will get a Study Cases where you are given a case and you have to do some EDA to answer the given questions.
I got around 10 replies from company and basically from then, my whole week is just for doing those study cases. I will say, it’s really hard. I didn’t get the 10 replies at the same time, but usually I got 1 reply and they gave me a study cases for me to do (usually the company gave you 2–3 days to do it but there’s some company that gave you almost 2 weeks!), and after I’m done with it, I got another study cases.
I also managed to interview with around 3 company which sadly I failed to get the job. But I managed to get my job on my 4th interview!
From my experience, usually a job application process for a data analyst is consist of:
- SQL Test
- Case Study
- Interview with Hiring Manager
- Interview with the Stakeholders
- Presentation of your Case Study
So yeah, that’s it for me! I have also written what I learn in my data science journey (but it still in Indonesian) so let me know if you wanted one in English!
I still have a long journey I should take to become great in Data Science, but I want to document it so I can take a look back and be reminded at how far I have gone :)
P.S : I started writing this after I read Travis Tang article! I never knew that we have ‘almost’ the same background, from Chemical Engineering to Data Science. I still have a long way to go but I hope I can catch up with him :) Also, shout out for Muhammad Imam Fauzan as the person who taught me how to code :p
Also, forgive me for the horrible grammar lol.
Good night and stay safe as always!
