You finished your program, you did your due diligence, yet you are still not able to kick start your career in data science. It probably doesn’t surprise you that you’re not the only one who aspires to fill up the challenging and rewarding role as a data scientist without any luck so far.
The moment you start searching through the various websites, blogs or perhaps even webinars that explain to you how you can find your first job as a data scientist, you still might end up knowing nothing. Due to the problematic nature of this query I wrote this article to shed some light and give answers on four of the most common questions so that you will be able to properly prepare yourself to find that dream job you’ve been searching for.
QUESTION 1: WHICH SKILLS AND WHAT TOOLS SHOULD I MASTER FOR MY FIRST JOB AS A DATA SCIENTIST?
I want to be honest with you upfront – there is good news and bad news for this answer.
The bad news is that most of the skills that you’ve been taught in university are, in 9 out of 10 cases, not applicable when it comes to fulfilling data science projects at the company you will work for.
In an article that appeared on KDnuggets the most sought after coding skills you should have proficiency in are: Python, Java, R, C++, and C respectively.
source: KDnuggets
Ultimately, it boils down to what kind of projects the company has initiated. Perhaps you will only need to use 2 or 3 of these languages, but the moment you are able to master one it will become much easier to learn another language on top of that, which improves your chance on getting a job as a data scientist.
Well then, what’s the good news I hear you asking? The good news is that all the tools mentioned above are free of charge. It is simply a matter of downloading and installing them on your device without having to pay a dime. This basically means that you can begin upskilling by launching your own data projects and prepare yourself for your future job.
QUESTION 2: HOW CAN I LEARN THE FINE ART OF DATA SCIENCE?
Even though the role as a data scientist is driven by the digitalisation of data, theory, and hypotheses I would advise you to read something more tangible, namely books. That’s right, books are (still) a great source to get focused on the details as to how you can and should use the above-mentioned tools to your advantage when it comes to the art of data science.
A few books that are highly recommended can be found here. After some online searching, I found out that the prices of these books range between €10 and €50. A small price to pay I’d say for increasing the chance of getting a rewarding job in data science.
The second way to grasp the fundamentals of Data Science is to attend webinars and watch online videos. Some of them are free and for others you might have to pay a modest fee of around €60 per month. I do advise you to look into the paid courses, though, as you will get bang for your buck.
QUESTION 3: HOW TO PRACTICE DATA SCIENCE, AND HOW CAN I GET REAL LIFE EXPERIENCE?
And finally, we arrive at the million-dollar question. I would like to guess that you feel some association with the image above. You probably feel that the moment you initiate your search to find a job in data science, the company you aspire to work for is probably searching for someone that has at least a little bit of experience in the field. But how do you get this experience if you have never worked before as a data scientist?
The answer is: having your own data science projects. This means that prior to applying for data science jobs you should decide on a business issue that is at play and identify how data science can be the solution to this problem. To give you some inspiration you can find some ideas right here.
Given that you are not fully experienced at this stage and you still need to learn the fine details that are at play, is very likely you’ll encounter various issues when it comes to coding. This is not something to worry about as you will find plenty of explanations to tackle these issues on forums where data enthusiasts gather. Some good sources where you don’t have to wait long for an answer and to exchange ideas are /r/Datascience and stackoverflow.
The most important thing that you should keep in mind is to be creative. Don’t launch your own project with a subject in mind that is either already solved, obsolete, or simply dull. Try to find something that is actually valuable to a business or society. Something that will blow your future employer away.
QUESTION 4: WHERE AND HOW CAN I APPLY FOR A DATA SCIENCE JOB?
First off, you need to start with writing a proper CV that stands out from the rest. This is easier said than done, so I suggest you take all the time you need. And if you can try and get someone who is already in the data science to proof-read it. If you don’t know anyone in your direct environment who could help you out with this, I strongly recommend to kindly ask if anyone from the subreddit mentioned earlier or Stackoverflow to have a look at it. (Don’t forget to leave out your personal details!)
Secondly, search for a company that enables you to learn and develop yourself continuously. This is by far more valuable than a company that would offer you a slightly higher salary where you won’t do exactly what you would like to do with the skills that you have obtained.
Having said this, you might want to search for a company that is medium-sized. Large multinationals are usually too busy to teach you new things and small companies usually don’t have anyone that can act as a mentor from whom you can learn. When I say medium-sized I’m talking about a company that has between 50 and 300 employees. In addition to this, another thing that you could also do is create a list for yourself that sums up some of the companies you would like to work for.
There you are, you wrote your CV, you found a company, all is set except that the company might ask you for a cover letter. You will be tempted to write something about the enthusiasm you have to get the role and this is certainly something you shouldn’t leave out. However, make sure you don’t dwell too much on your enthusiasm and ensure that you also include some practical details as to what you would like to do for the company in the first weeks when you are hired.
Convey the power and the effect of your ideas, write about your projects, and represent yourself in a way the company has no other choice than to hire you. You worked very hard to get where you are after all!
Source: https://www.davisnolan.com/
Author: Dominika Wojtanek
