5 Ways to Land a Data Science Job (Without Prior Experience)

Data driven jobs are filling the job sphere, simply because the sheer quantity of data generated every day is massive and growing every day. It is because of this that businesses all around the world are incorporating data and information into their marketing and operations strategies. The necessary additive to this extra data and information is the requirement of a person who possesses the needed skills and knowledge to understand, analyse, and utilise the data which is relevant to the company. Because of this, data science has grown in popularity as a profession.

When looking at professionals who work in data science, their previous experience and possible degrees could be overwhelming; however, in this article I will outline 5 steps to help you on your way to landing a data science job, without any previous experience.

1: Assess Yourself

This step is key when entering any new job sphere, but essential when talking about data. It is important in this step to ask yourself questions. If you were a company, why would you hire yourself? If companies are not hiring you, ask yourself why. Ask yourself what you currently know about the data science world, what you need to learn, and what you could bring to the field that is not already there.

2: Master These 3 Skillsets: Mathematics, Programming, and Communication

Mathematics : The importance of mathematics and computing in data science boils down to the need for statistics and probability in data analysis. So it is not general but specific maths that is needed. It is important to have a firm handle on this knowledge and how it operates in the real world.

Programming : This is an interesting one, as I would stress to not make yourself anxious with an overabundance on programming language and knowledge needs. Jean Rivers PhD, an accomplished data scientist at Writinity and Last Minute Writing, gave her advice to up and coming data science hopefuls, saying, “Though there are an infinite amount of programming languages, data science prioritises ‘Python’ and ‘R’. As a beginner, focus on these two; and when you eventually gain confidence in these, move on to more advanced and varied scripts like Java, for example.” These scripts can be learnt online; and remember, practice is the key to all coding.

Communication : Though technical skills like mathematics and coding are important, communication of these results is crucial to finding a place in the data science world. Discovering and deciphering data is important, but if you do not have the skills to present and explain your findings, your skills will eventually become obsolete.

3: Real-World Practice

Though learning the relevant knowledge and practicing your craft is important, real world practice is where it all comes together! The more experience you have in real life data analysis; the more realistic your dream of working in the data science sector will become. There are even competitions and challenges available online to give you practice, look for them!

4: Make Connections with Leaders of Industry

As Brad DeAngelo, a full-time career coach for Draft Beyond and Research papers UK, once noted, “As with any industry, connection is key! Your network is your stairway to success. Whether you have a network established already, or need to build one entirely from scratch, it is a vital stepping stone to establish and recognise your network.” And he is right! In addition to this, taking advice from leaders in the field of data science will only make your knowledge more advanced and your skillset better overall. These initial connections will help you further down the line with your career as well.

5: Get to Grips with Reality -

At the moment, data research and analysis is one of the highest paying fields at the moment, and it is no surprise that that is the case. Data and information has become a form of currency, and a valuable one at that. Because of how vital and business critical this is, as well as how sensitive data is as a subject; less than ideal candidates will not even be considered. The vitality and integral nature of the field has made it a competitive job field. Saying that, motivated and committed candidates vying for these positions can do very well; even with little prior experience.

With the relevant kick-starter knowledge and tips, as listed previously in this article; anyone committed and dedicated can work their way into what is now one of the most profitable spaces in the modern workforce. Although at first it might seem daunting to venture into a field where it seems like you are at a disadvantage, it can be extremely profitable if you are able to commit and put in the work. Hopefully, these 5 tips will enable you to begin drawing your own personal roadmap into the data science world; one of the fastest growing and emerging micro-economies the world has ever seen.

About the Author :

Ashley Halsey is an article writer and blogger for Lucky Assignments Bristol and Gum Essays, and she is regularly involved with different projects for each around the world. She is also a full-time mother of two girls, who enjoy following her on her travels.


very informative and encouraging write up!