Switching into data science is not easy. Today I'll talk about the steps I took to switch from
aerospace engineering into data science and I'll talk you through how you can transfer your skills
into a data science role. I'm Samanvay, a data scientist living in Sydney,
Australia. If you don't know already I studied aerospace engineering, then I became a data
scientist around five years ago. I made the move so that I could learn new skills to apply into
different industries. For a full recap, check out this video I made a couple of months ago. Today
I'll talk about how you should think about your career transition into data science, especially
if you study engineering or work in a different field. I'll talk mostly from the perspective of
a recruitment manager so that you can set yourself for success as you apply for jobs in data science.
When you're looking to make a change you need to be in the right mindset. So what do I mean
by that? The first question on the recruiter's mind will be why do you want to go into data
science. You need to be well prepared for such a question. Given the boom of data science recently,
there's lots of candidates approaching data science recruitment managers which means that
they have lots of graduates coming to them with no experience in data science. So you really need
a solid reason as to why you're looking to make the switch. Answering this question is essential
to make sure that you're going in it for the right reasons. So I would suggest spending some time and
writing down all the reasons that you want to get into data science. For me it was a love for coding
and solving large-scale problem using data. So figure out your reason for being a data scientist
and have your origin story prepared. At the end of the day getting a data science job relies on your
ability to sell yourself as someone who is skilled enough and passionate enough to get the job done
well and it's really important not to make anything up. You need to be as genuine as
possible because hiring managers are very good at looking beyond the smoke screen. So be very
careful. The next part is to think about the transferable skills that you bring to the table
when you're looking for a data science job. When I was making the switch from engineering
I knew I had solid problem solving skills and I had the ability to learn new skills quickly
which meant that I tried to leverage those skills and also display them across my resume,
Linkedin and the interview. So it's important to be very transparent with what your strengths are
and what will enable you to excel in the role of a data scientist. So when you're preparing
your resume be sure to highlight all the data related skills that you're going to be using
on the job and sit down and have a think through what your strengths are which will enable you to
excel. I'd also recommend doing a couple of data projects and having them in Github and
make sure you list them on your resume because that shows your ability to proactively learn
about a field that you want to work in because at the end of the day a company will hire you
for your curiosity and your ability to learn. If you're a professional you should think about your
hard and soft skills that you've developed in your professional roles because that will help you set
yourself apart let's say that you're a healthcare professional looking to make the move into data
science so one easy way to set yourself apart is to apply for data science positions in health tech
industry because right off the bat you're very different from the rest of the candidates and
you've got the healthcare experience to excel in a role like that because domain expertise in data
science is way more important than your coding or maths skills because in a lot of industries
the challenging part is to quickly ramp yourself up with the specific knowledge of the domain. So
think long and hard about what skills do you bring to the table because I can guarantee you that all
the roles that you've done previously are going to be applicable to data science because it's such a
broad skill set that you need as a data scientist. You'll be doing everything from technical coding
all the way to stakeholder management. So there's always a place for your skills that you have spent
couple of years honing in. Last piece of advice I've got is to be yourself in the interview
process. As someone switching fields you might be very self-conscious as to how much you know and
you don't know in the field of data science. Occasionally you might feel like an outsider
but don't be put off by that. Data scientists are quite diverse in their backgrounds and
their experiences and this makes for a generally welcoming and open-minded atmosphere so it's okay
not to be able to answer everything in the interview answer what you can
and admit that you don't know something because it shows them a willingness to
learn and be coachable which is way more important than the hard skills you're bringing to the table
because often you'll be working on lots of problems where you have no clue where to start
but your job will be to find the answers. That's it for this video hope it helps you with your
job search. If you enjoyed the video then smash the like button and I'll see you next time.