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.
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:
- What skills are required for data science, and how should you go about picking these up? (Chapters One, Two and Three)
- From a job market perspective, what steps can you take to maximise your chances of gaining employment in data science? (Chapter Four)
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.
CHAPTER ONE: WHAT IS DATA SCIENCE?