How to Become a Data Scientist – Part 1

How to Become a Data Scientist – Part 1

How to Become a Data Scientist – Part 1
Check out this excellent (and exhaustive) article on becoming a data scientist, written by someone who spends their day recruiting data scientists. Do yourself a favor and read the whole way through. You won’t regret it!

I am a recruiter specialised in the field of data science. The idea for this project arose because one of the most common questions I am asked is: “how do I obtain a position as a data scientist?” It is not just the regularity of this question that got my attention, but also the diverse backgrounds from where it was coming from. To name a few, I have had this conversation with: software engineers, database developers, data architects, actuaries, mathematicians, academics (of various disciplines), biologists, astronomers, theoretical physicists – I could go on. And through these conversations, it has become apparent that there is a huge amount of misinformation out there, which has left people confused about what they need to do, in order to break into this field.

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I decided, therefore, that I would investigate this subject to cut through the BS and provide a useful starting point for anyone looking to move into commercial data science – whether you are just starting out, or already possess all the necessary skills but have no industry experience. And so I set out with the aim of answering two very broad questions:

Why am I qualified to write this? Well, I speak with data scientists every day and to be an effective recruiter, I need to understand career paths, what makes a good data scientist, and what employers look for when hiring. So I already possess some knowledge on the matter. But I also wanted to find out directly from those who have trodden this path, so I began speaking with data scientists of different backgrounds to see what I could unearth. And this took me on a journey through ex-software engineers, an ex-astrophysicist and even an ex-particle physicist, who – to my excitement – had worked on the discovery of the Higgs boson.

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CHAPTER ONE: WHAT IS DATA SCIENCE? Different Types of Data Science

So you have made the decision to become a data scientist. Great, you are on your way. But now you have another choice, which is: what kind of data scientist do you want to become? Because – it is important to acknowledge – while data science as a profession has been recognised for a number of years now, there still isn’t a commonly accepted definition of what it actually is.

In reality, the term ‘data scientist’ is regarded as a broad job title and so it comes in many forms, with the specific demands dependent on the industry, the business, and the purpose/output of the role in question. As a result, certain skillsets suit certain positions better than others, and this is why the path to data science is not uniform and can be via a diverse range of fields such as statistics, computer science and other scientific disciplines.

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The purpose is the biggest factor that dictates what form data science takes, and this is related to the Type A-Type B classification that has emerged (see here: What is Data Science?). Broadly speaking, the categorisation can be summarised as:

We may see further evolution of these definitions as the field matures, but for now, we will continue this exploration with a look at the ‘science’ in data science.

Owning Up To The Title

All scientists work with data, so in a sense all scientists are data scientists.

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