
It’s been 2 years since I last delivered mail. Quite frankly, I am not missing it, in fact, the thought of me being a mailman seems absurd to me. But it definitely happened, I was first working for Royal Mail which is Britains postal service and courier, before switching to the mailroom at the City of London’s Guildhall.
With little Education and lack of a network for guidance, I staggered my way into Data Science. Although I still have plenty to learn, I am at a point now where I can look back at where I was and be proud to say I’ve accomplished something I said that I will do, even though the odds were stacked against me.
Previously, I’ve written numerous articles on learning Data Science:
How to Learn Faster for Data Scientist
The Reason You’re Frustrated when Trying to Become a Data Scientist
However, I’ve never directly answered the question of "How do I successfully transition into Data Science?" which is exactly what you will learn from this post (from my experience).
Use Your Difference To Your Advantage
If you are currently in a field where there is no direct translation into Data Science, you are very unique and you can use this to your advantage. This is not to say that people who are in related fields (or academia) are not unique, instead what I mean is that you are unique in a sense that you have not followed a direct path, so you’d have to show a lot of character to compete in the job market with someone who has.
In order to use your difference to your advantage, you have to be able to package your experience in a way that sits well with the hiring manager and company. You may not have the academics or experience to back you, but something undeniable you have is grit, but you must package this grit into something tangible.
"You’ll always come across much more interesting when you’ve come from a totally different world"
Think about it, if you saw someone that built a car from scratch and they have not followed a linear path into car manufacturing, but the car is as good, or if not better, than someone who did, wouldn’t you be intrigued by how they did it? Wouldn’t you be happy to have this person on your team, knowing that with limited resources and untraditional education/experience, they are resilient enough to seek solutions? Exactly.
The key here is to package your difference, there is no point stating on your CV "I have a lot of grit" or "I am willing to learn" because these are generic things that I personally think should be expected of someone in a technical field.
Rise above Imposter Syndrome
Recently, I’ve begun to notice that imposter syndrome is not only for people that aren’t quote-unquote "qualified" to become Data Science because I’ve met people that have been studying math, computer science, stats, etc that are suffering from the same feat. In fact, I’ve spoken to people that work as data scientist that say they feel like they are faking it.
"To successfully pivot from your career into Data Science, you must overcome the mental blocker that whispers in your ear that you are not good enough."
Impost syndrome can have you stagnant, hopeless and questioning yourself. However, part of transitioning into Data Science is about recognizing the qualities and experiences that make you qualified for the role you desire. For me, being the captain of every single football team I’ve played for is what gives me the confidence to be vocal, and as a postman I developed the ability to be extremely thorough and pay close attention to detail which helps me when I am trying to code an algorithm (such as in the Algorithms From Scratch Series) or when I am carrying out error analysis and more.
Another way to overcome imposter syndrome is to convince yourself that you’ve got the grit to figure things out. I personally believe the best way to do this is by doing your own end-to-end project.
Find someone that’s been in your Boat
You may be glad to know that you aren’t the first person in the world transitioning from another field into Data Science. Find someone else that has done it before and listen to how they did it – This is not a personal plug.
The person does not have to have transferred from the exact same field as you. I am still yet to see another ex-post man turned Data Scientist, but I wasn’t looking for that. I was just looking for someone that has made the transition.
"Hearing from someone else that has taken the path you are on will give you something to aspire to and fuel your passion".
A funny trend I’ve noticed from the podcast I listen to (Learn more about these in How I stay up to date with Data Science) is that many people do not feel as though they’ve taken a definitive path into Data Science and that they’ve almost stumbled their way here. This makes absolute sense!
Data Science is a very new field and is not very well defined at the moment. There are discrepancies from company to company about what a Data Scientist is, hence many feel as though the path they’ve taken to end up where they are has been non-linear. You aren’t the first and will not be the last, but you should definitely stand on the shoulders of one that has gone before you.
Wrap Up
Transitioning careers is much more difficult and scary than changing employers. However, I believe these precursors are what helped me in my transition phase and can be of great benefit for anyone trying to transition into Data Science.
If you think there is something I’ve missed, leave a response or connect with me on LinkedIn…
Kurtis Pykes – Data Scientist – Freelance, self-employed | LinkedIn