Given my current circumstances – being made redundant recently – I’ve been considering whether I truly want another permanent role, but this time as a Data Scientist rather than a Machine Learning Engineer, or whether I have what it takes to go solo as a freelancer/contractor.
Nevertheless, it is important I continually develop my skills and I know how important real-world experience comes into play when discussing personal development.
The question people often ask is "How do I get a Data Science Job without Experience?" however I thought if I could flip this question on its head, not only would I develop my skills and gain exposure to the real-world of Data Science, I’d make myself much more employable in the process. Therefore, the reverse of this question would be:
"How do I get Experience as A Data Scientist without a Job?"
Volunteering
I know this one is tough, but volunteer positions are much more easily secured than an internship, and they are a sure-fire way to boost your employability, especially if you have no experience. Of course, if you have priorities such as a family to provide for, a mortgage, etc, then you may need to supplement this with some part-time work to help ensure you are keeping up with your responsibilities.
Being a volunteer Data Scientist also highlights extremely important skills in your character such as commitment, initiative, and a strong work ethic – at the end of the day you will be receiving no financial gratification from a role that someone else may be earning 6 figures doing – which are all very valuable traits that are appealing to prospective employers.
To further add, from my experience of volunteering throughout the month of August, I believe there is a lot to say about the transferable skills that I feel volunteering helps to develop, for instance, teamwork, confidence, time-management, adaptability, communication, and organization.
Build Your Network
I feel as though I rattle on about building a network in every post I make, but honestly, it is that important.
When you are lacking in experience, who you know can be just as important as what you know.
I’ve mentioned time and time again, I secured my first technology job through my network, and I landed my first volunteering role through my network, and regardless of whatever I decide to do next, I am sure my network will play a major role. My network has been what has pushed me so far in this field hence why I personally put such heavy emphasis on building it.
If you are unsure about how to build your network in Data Science, you may want to read about The Most Important Data Science Project.
If you are at university, make the most of the contacts available to you before you graduate. If you are already employed, ask them if they know of anyone that may need a hand with their data as you want to improve your skills in your down-time.
Social Media has made building and maintain a professional network extremely easy. All you have to do is be present, consistently – whether it’s contributing to open-source or simply engaging in other people’s posts or both. Be present!
Emphasize the Skills You Have
A few LinkedIn examples of people I believe do this extremely well are Abhishek Thakur, Kate Strachnyi, and Susan Walsh.
Focus on the skills you have, that’s not to say you shouldn’t develop other skills, but you’d feel as though you are chasing all the time because Data Science is a large field and there’s always going to be things that you don’t know.
Using Job Descriptions as a comparison to identify the skills you have that make you employable is a good idea.
Recently, I was speaking to a really helpful recruiter that has lots of experience in the field of Data Science, and he asked me "What type of Data Scientist are you?". At first, I was stumped so he gave the analogy of different types of Strikers in football; In Football, there are strikers that like to hold the ball up to bring others into play, there are strikers that prefer to run in behind defenders, strikers that like to mix the two, etc.
Knowing the type of Data Scientist you are or would like to help emphasize the skill you have!
Are you a Data Scientist that emphasizes on Machine Learning?
Are you a Data Scientist that emphasizes on Deep Learning?
Are you a Data Scientist that emphasizes on Data Cleaning?
Do you focus on NLP?
Are you a Data Scientist that emphasizes on Data Visualization?
In my opinion, having a skill you can emphasize on sets you apart from other Data Science, but it is no reason to not have insight into other areas – someone doing NLP may benefit from learning Computer Vision.
Wrap Up
A job is obviously the best way to build up your experience, especially if you are in an environment where you have experienced Data Scientist around you. Deciding to go out and build up your experience alone is definitely the tougher option, hence I don’t recommend it for people that aren’t willing to put in the effort to take this route. On the other hand, I believe taking the initiative to get experience on your own yields better returns in the long run – If done correctly – and it is definitely someone that is willing to invest the effort in their development should take.
Let’s continue this conversation on LinkedIn…