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Let’s not lie, data science can be hard. Whether you’re embarking on a period of self study or are making your first tentative steps into the field it can feel daunting. If you’re reading this then I’m assuming you're either thinking of entering the field or have some analytical experience and are transitioning towards a data science role. If you have exposure to experienced data scientists at your place of work or you follow them on social media it can seem like there is a huge gap between what they know and where you are.
There is however, ways you can tell whether you’ll enjoy working in data science and if you’ll actually be good at it, that hopefully will keep your confidence and motivation high as you navigate your way through your studies and early career.
Now data science isn’t all roses and isn’t without boring or stressful moments but if any of the below are true for you then it’s a good indication that you’ll find some satisfaction working in the field.
I’ll make no bones about it, real world data science can be hard. From data that is filled with holes and inaccuracies that doesn’t want to easily give up it’s insights to building models and tools that are accurate enough and useful data science is full of challenges.
If you enjoy working in an area where things don’t always come easy but you enjoy the satisfaction of working hard and possibly succeeding where others have failed then data science can give you that opportunity.
If you're a problem solver, data science can be hugely satisfying. Often there will be macro problems that businesses have been battling with for some time and it’s not until someone with the necessary data skills comes along and extracts insight that real progress can be made.
At the same time you will experience micro problems such as trying to debug algorithms or diagnose data inaccuracies. Having to intricately pick through the detail and solve these problems will be a regular occurrence.
If that sounds like something that will make you jump out of bed with excitement each morning then this could be the career for you.
Data science is a constantly evolving field. Different variations of algorithms are being developed at pace and cutting edge solutions to problems are released regularly plus even new sub-fields can spring up from time to time. You will always have something to learn and you will never be in a position to say I know data science or I know machine learning.
If always having the possibility to level up, be able to utilise a new method to solve a problem or get stuck into a new piece of software excites you then you’ll always have that option with data science.
I’m going to be blunt, you will have set backs. As you study you will have times where you think you’ll never be able to get your head around certain concepts, that everyone else can see things you can’t.
When you begin working on projects in real world scenarios you will get the feeling that your work is never going to lead to insight or a useful solution.
If you can manage these disappointments and push on or even better channel them into improving yourself then this will hold you in good stead as you progress through your data science career.
Now you have an idea of whether you’ll enjoy being a data scientist, will you actually be any good at it? The points below are all attributes shared by successful data scientists. If you have some of them already then you likely have the foundations to also be a successful data scientist.
Do you enjoy being in the detail, prefer to make decisions based on evidence and always looking to improve things? Successful data scientists are highly logical people. Whether they were always like this or developed that skill with experience is another question but if you already have this kind of thought process when you approach your work or other things in your life then that’s a good fit for working in the field.
A data scientist might be highly skilled in terms of technical ability but being an expert coder and having deep knowledge of a wide range of algorithms and methods is only part of the equation in becoming a successful data scientist. What matters is creating solutions that are useful and add values, whether that’s to the company you work for, a customer or even just yourself.
Successful data scientists are also experts at being able to filter out the noise around a problem and identify what will make a difference and also develop a solution that fits. It doesn’t have to be an all singing neural network using millions of training examples. It can be as simple as a small data set transformed in a certain way.
Again, this is a skill that can be developed with experience but some people already have this from exposure in other areas of business or research.
If you follow any successful data scientist you will probably notice that to these guys data science isn’t just a job. While they likely have full time occupation that they are dedicated too they likely also spend time competing in data science competitions, writing articles, doing their own research or just spending time building interesting things.
If your motivation for moving into the field goes beyond just finding a 9-5 gig then that will give you a competitive advantage in the field in the long term and ensure you’re always pushing beyond your current skill set towards mastery.
Hopefully that gives you an indication of whether you'll be enjoy working as a data scientist and if you'll be good at it. It's not neccesaary to have all of the attributes in this article but and there maybe other values not listed here that can give you a competative advantage in the field. Not everyone has the same skills and are from the same backgrounds so just keep developing.
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