Data Scientist in Python
Which skill should I get good at? There is so much to choose! Should I even get good at anything? Help?!
After 8 weeks and one day of sweat and lots of junk food I’ve made it to 100%!
Before I’ve fantasized about this day, how I would feel. I have to admit it was most definitely a modest party, with some ice cream.
So am I a unicorn already?
Well sadly, a few days later I’ve started to feel a bit sad, and that is mostly because I have no clue about what to do next. I know I can refine my portfolio (which I even did not put on github yet).
IMPORTANT: It does not matter who you are reading this, if you have (big) data dreams that can make me sparkle again, please share them here. This is your place to let your data hopes and dreams out. Let’s inspire each other through great work.
Well, If I’m not a unicorn who am I then? let me share a very brief introduction:
I’ve been a professional chess player for a few years, but the pay is becoming less and less, and with Corona, the tournaments have stopped completely. Besides I have authored some books on chess openings and my education is a MA in Philosophy.
Now, math is amazing, and data became an immediate addiction. (Un)fortunately I love many many things, which makes it difficult to choose between what to do.
It’s not about the right skills it’s about the problems you can solve.
At this point I believe I’ve been reading a ton of articles on what I should know, what the industry needs etc. like probably most of you have read. The above quote is the thing I see the most.
So what are the problems encountered most?
I have scrolled through many pages of upwork and freelancer.com, only to find that there are actually a lot of data scientists working for $5 an hour. And those people are claiming to have years of experience in the field. This made me almost give up my freelance data dreams already.
It’s mostly Business Intelligence and Big data problems.
And what about skills to learn then?
Browsing through job descriptions all the roles seem to be very different. Python, R and SQL are asked for most. But then there are many things to learn after hitting 100%:
- Scraping, an art in itself. This is really funny, you won’t regret clicking this!
- Kaggle, although there seem to be only beginner’s competitions and competitions requiring big GPU’s for image processing.
- TensorFlow or PyTorch, probably on the list as well
- Cloud computing, most notably AWS and Google cloud services.
- Tableau, the best visualization tool ever (it seems)
- Big data, building on the Apache Spark introductory course seems to be a great idea as well. (How do I get the computing power and disk?)
- Power BI
- The DQ Data Engineering path
I’m glad you’ve made it to the end of this terribly desperate post . I really hope you can offer me any advice! And who knows, we might actually start having a very valuable discussion for everyone on this platform