Welcome to this special Article, where you’ll learn everything you need to know that How to Get Data Scientist Job in .
Data science is one of the fastest growing industries over the last decade, Data science has become an extremely appealing career path.
Well, we are here to give you the answers and then point you to some extra resources that will help you prepare for Data science success.
We’ll go over education experience skills, and finish up with a cohesive plan on the steps you need to take to start your journey as a Data scientist.
Of course, all the information is based on empirical research statements by employers and Data science and a dash of our personal experience. So let’s begin,
In previous Article, we’ve discussed the best degree for an aspiring Data scientists. To recap, any form of postgraduate degree in a quantitative field gives you a pretty good chance of success, with computer science being the most represented major.
Apart from an education, you also need some sort of experienced credentials to your name. To understand the methodology we used
For reference, the results suggest that roughly 35% of current Data scientists have already had a job in the same position, which is actually fantastic.
Whoa. But how is this good news? Well, the remaining 65% had a different occupation prior to that. Therefore, roughly two out of every three Data scientists are on their first Data scientist job in the field.
Therefore, it’s safe to say that becoming a Data scientist is a very achievable goal. However, don’t expect to become a Data scientists right after school.
Either way, to land even an entry level position, you need some previous experience elsewhere. This is a testament to how demanding the position of a current day Data scientist is nowadays demanding and hard to get, but not impossible.
What steps should you take?
According to employers and recruiters, if you want to succeed in the field, you also need to know three things,
- The tools
- The Data
Let’s break this down.
Knowing the tools means confidence and working with the most popular software on the market. Those are undoubtedly Python And R, It is important to note that Excel is still a main prerequisite in any job description in the field.
This means you need to understand where your Data is coming from, what are the best ways to process and pre process it, and most importantly, how to extract actionable insights from it.
Therefore, you need some coding pedigree, regardless of whether it’s in our Python or another scripting language. The statistical and analytical skills are there to help you understand and interpret the results before translating the raw numbers into insights.
Usually, to land an entry level job, you don’t need to excel in all categories. And being okay in two of the three is fine, as long as you’re great at programming.
Finally, it’s crucial that you know the business before you apply for a job in a given company. You must find out which aspects of Data science and what skills are necessary to land a position there.
And by all means having market expertise in this specific field, is always a bonus. So the more holistic your understanding of the Data and the industry, the more well suited you are for the position.
Overall, employers are looking for somebody with good coding statistical and analytical skills. Aren’t we missing something? Of course, employers are achievement oriented.
So they’re always looking for certain transferable skills in a candidate, that add value to the company, taking initiative setting, challenging goals, and making efforts to exceed those goals.
Some examples of transferable skills you should develop interpersonal skills also translate easily across various industries and contexts, So make sure you got that covered.
Other highly appreciated skills in this category include the ability to learn from experience, and be the propeller of positive changes, independence, self direction, and accountability.
Therefore, make sure your resume includes projects or internships where you work with others on top of some evidence of your proficiency in coding.
So we discussed what you need to know what skills you need to have. But now it’s time for the what you need to do part in highly competitive fields, such as Data science, who you know, could be just as important as what you know.
This is especially true when you’re trying to break into the field and find somebody who is willing to give you a chance even at a junior position.
Getting a recommendation from your previous boss, or a referral from an employee of the company you are currently applying at is a surefire way to boosting your chances of getting hired.
And the tried and tested way of getting these is through networking. One good approach is to use handshake and similar sites or alumni from your school post job ads.
This way, you can find interesting potential employers who you want to interact with, drop them an email, ask them for an informational interview.
Give them your details and ask specific questions about what their company does. By doing so, you’re making a solid good impression.
Because you know or you want to learn the business, and you’ve done your research. Sometimes you won’t be able to get direct contact information through the website.
So you can check out your school’s alumni directory, and you should be able to find at least an email, a phone number or LinkedIn profile, and all you have to do next is reach out.
Alternatively, you can meet people in the field by going to local conferences or lectures about Data science.
Universities and Colleges frequently organize the events or the sort which are often open to the general public. In addition, independent Data science societies, also sponsor or organize control group meetups, where they discuss the applications of DS and specific fields, like medicine or finance, for example.
Just remember, the more invested you look, the higher the chance that these people would want to keep in touch. So try to stay enthusiastic and curious. Of course, knowing the right people will get you far, but in most cases won’t get you the job.
Even with a referral or recommendation, you still have to go through a job interview. Your potential employers can always test your statistical skills with a written exam and your programming skills with a remote task.
However, you only get the face to face interview to present your coherent communication skills. So make sure you highlight them in the best possible way.
Of course, Data science incorporates multidisciplinary aspects of various fields, so it can be difficult to prepare for everything.
What you need to do to land an entry level job as a Data scientist.
For starters, you should earn at least a graduate degree in a quantitative major like computer science, then you need to gain experience in a field tangent to Data science.
So a job as an analyst or an It is a good way to go about it. An internship is also a viable option if you’re still studying. knowledge about coding, working with Data and the line of work you’re interested in is vital to so ensure your resume showcases all of that.
Also try to highlight some essential transferable skills in your resume, like drive for the business and ability to work in cross functional teams. conduct some networking and try to earn a recommendation or a referral for a specific position.
On a final note, make sure to showcase certain measurable qualities you possess like communication skills and curiosity during the interview.
In our opinion, doing all of this will give you a great shot at securing an entry level job as a Data scientist. If you enjoyed this Article, don’t forget share. And if you’d like to become an expert in all things, Data science, then Read our other article.