Data Scientist Job — Is it worth the sacrifices made?
Data Scientist Job — Is it worth the sacrifices made?
Long story short — It did (at least for me)
OPINION
Long story short — It did (at least for me)
You are opening the web and find out that Data Scientist is the sexiest job.
The web said you would get paid ~$100.000 annum as Data Scientist.
You interested in the prospect and started to find a way to become a Data Scientist.
Opening every web tabs,
reading many articles,
collecting countless e-books,
messaging people on LinkedIn,
watching courses on YouTube videos,
sign up for online classes,
attending offline Data Science Bootcamp,
competing in the Kaggle Competition,
and so on.
You sacrifice a lot — time, money, sleep, mental, relationship, etc.
Then you feel ready to be a Data Scientist.
You fill out the job application — Entry Level jobs with thousand applicants,
waiting for the calls,
few companies called or nothing at all,
rejected,
you become more creative,
try to find a social connection,
or applying for internships,
and keep trying.
Even after so many things sacrificed, the only people secure the job position are few.
Many either need to wait for another chance or just give up.
Not everybody is going through a similar ordeal, but some would feel familiar.
Is it worth the sacrifices made?
Let me try to explain what do you need to become a Data Scientist.
“Then, maybe, just maybe, Data Scientist is the job you worth sacrifice for.”
What does it take to become Data Scientist?
There are many essential skills to become a Data Scientist, but which one is take the cream?. Let’s see the top 10 skills surveyed here on KDNuggets Polls.
As expected, many of the skills are technical skills. Python and Data Visualization both take the first and second place, with Critical Thinking Skill next. For a moment, let’s ignore the non-technical skill such as Critical Thinking and Business Understanding. How long did it precisely for us to learn all these skills and how much we need to pay? Let’s take a few samples out there.
Online Courses
Let’s say we learn 4 hours per week (where often a recommended time in the online courses).
IBM Data Science Course in Coursera provides a course for Python & SQL, analyze & visualize data, build machine learning models. ~10 Months. Cost: $USD 39 per month
Data Science Online Bootcamp in Udemy promises to learn about Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning. ~28 hours of online videos. If we learn 4 hours per week, it would ~ 2 Months. Cost: ~$USD 200 but often time discount to ~$USD 12
Data Science track on DataCamp, which courses including Python, Data Visualization, SQL, Machine Learning, and Statistics. 100 hours ~ 7 Months. Cost: Standard subscription $USD 25 per month or $300 Annually
Bootcamp
What about Offline (or Online, but extensive) Bootcamp with the trainer? How long they promise that you could become a Data Scientist?
Metis Data Science Bootcamp in the US curriculum says you would learn Python, SQL, Machine Learning, and Statistics (and many more). ~12 Weeks or 3 Months. Cost: Full Tuition $USD 17000
New York Data Science Academy curriculum includes Python (and R), Data Visualisation, SQL, and Machine Learning. ~12 Weeks or 3 Months. Cost: Full Tuition $USD 17600
Springboard Data Science Track with curriculum Python, Data Visualization, SQL, and Machine Learning. ~6 Months. Cost: Pay Upfront $USD 7500
Singapore Hackwagon Data Science courses with a complete course in Python, Data Visualization, Machine Learning, Math, and Statistics. ~7 Weeks x 3 Courses or around ~ 5 Months to 6 Months. Cost: $SGD 2000 per course x 3 = $SGD 6000
From the samples above, we could see that online courses offer you many hours of online videos or courses. Many recommend studying them for more than six months (It depends on how long you want to spend each week thou). This is reasonable because online courses are static without any interaction with a mentor, so you need a longer time to understand each concept. The main advantage of online courses is that they are cheap; Almost everybody could afford it if they spare some money although it becomes a problem as well. While it’s cheap, it only builds you a momentary knowledge without proper mentoring — no direction.
Furthermore, many employers did not see online courses as an asset, except if you already have a relevant degree or experience. In my personal opinion, Online courses are worth as much as their price — It is good to improve/review your skill, but don’t rely solely on this to be a Data Scientist. You could try to learn the skills by using various books or just reading the documentation as well, but I am not sure how long it would take to master the necessary skills.
How about Bootcamp? We could see that it is way more expensive. Like, really expensive. It is because Bootcamp offers a few things that online courses did not have, namely professional lecturer, personal mentoring, intensive schedule, and connection (Although I know some Bootcamp did not have an experienced employee and/or connection). The question is it worth it? The answer is Yes and No. Yes, because for a newbie, you would need a direction, professional review, and connection to break into a Data Science and No because you could get all the necessary skills from books or online courses. For further consideration as well, in today’s condition is hard to guarantee someone’s employment, as much as the Bootcamp promised you a job after completing the courses; take it with a grain of salt.
Now, what I explain before all are about the technical skills. Where did you even get the non-technical skill such as Critical Thinking, Communication, and Business Understanding? No Online Courses or Bootcamp teach you this. For this, I haven’t mentioned the other way as well to get the necessary skills; it is by obtaining a degree and/or Professionally employed, just like me.
Why many employees like aspiring Data scientists to hold a degree? This is because there are skills you only get by following courses in College/University. I didn’t necessarily mean you need a Ph.D. to be a good data scientist — Even Bachelor is good enough if you following the courses properly. It will teach you Critical Thinking and how to communicate, maybe Business if your degree is in line with the employer business. Although, it would take a long time and higher cost compared to what I lay down above. My education time to Master’s Degree takes six years with three-four Years of professional as a Researcher, and a few months to review my technical skills once more before becoming a Data Scientist. Yes, in total, I need around nine-ten years preparation just to step into the Data Science world.
In any way you choose, prepare to spend lots of time and money on obtaining the necessary skills. There is no free lunch, after all. You need to give something in order to get something. Also, there is no guarantee to secure a data scientist job after all of that. You need to prepare a tough mentally for dealing with rejection that comes.
Is it Worth the Sacrifice?
I sacrifice a lot of money, times, sleep, and relationship. I spend a lot of money and time in the wrong place. I put down offer to hang out with friends or even a relationship just to focus on learning the Linear Algebra. I spent my awake time solely only to improve my skills. Would all of it worthy?
Now, if your only aim is the salary, Data Scientist is not worth the sacrifice at all. There are still many jobs that pay better with similar or less time and money spent to master the skills (or even fewer skills to learn). For example, Software Engineer, Full Stack Developer, Lawyer, Pharmacist, or even Pilot. There are still many kinds of employment out there that are better to spend the time with a better salary and awesome sounding-names.
If you become a Data Scientist, your workflow roughly would look like this.
Don’t imagine as a Data Scientist we would work on creating a machine learning model or magically predict what comes next. Most of the time, we only collecting data, creating a report, using a statistic to make sense of what happens, presentation, and exploring data. It still depends on what business your company is, but often, it only looks at what’s above.
If you can’t imagine yourself working collecting and looking at the data all the time, then don’t be a Data Scientist. The Machine Learning model is cool, but don’t stick on the job you would regret. The sacrifice is just too big.
However, if you love looking at the pattern, do not mind getting dirty on assumptions, having patience in exploring data, love analyzing, having a data literacy talent, and excellent at communication. Then, maybe, just maybe, Data Scientist is the job you worth sacrifice for. You need to know what you sign up for after all before making that sacrifice.
Conclusion
I love my career because I love exploring my data, looking at the pattern, getting a piece of new information, creating a hypothesis, testing my suggestion, and so many more that I can do with data. Yes, I love playing with Machine Learning as well, but it is not solely what I enjoy from my job. The career prospect, of course, great as well.
What I want to say is that you need a lot of sacrifices to get into Data Science. Before you make all of that, make sure that the sacrifice is worth it. For me, it was worthy.