Let's talk about money. Honestly I wanted to get more coins for that opening shot but
I couldn't really find anything. Onto the video topic of today. How much does a typical
data scientist actually earn and what can you expect to earn once you graduate from uni? So
this video might be useful to you if you're thinking of immigrating to Australia or you're
a student currently studying data science in hopes of embarking on their data science career. Let's
get started and make sure you watch till the very end so that you can find out exactly what the peak
earning potential of data scientist is. I'm Samanvay, a data scientist living in Sydney,
Australia. For the benefit of my international viewers salaries in Australia consist of two
components. Firstly you have the base pay then you have super which is a compulsory contribution to
a retirement fund by your employer this amount. From this year onwards, it's about 10% of your
base pay. For example if the base salary is $100K then the total salary package would be $110K.
Depending on the company you work for you can also get a bonus. This can vary anywhere from 5% to 15%
or even higher based on the industry you're in. Today we'll only talk about base salaries
or base + super salaries. Now let's talk about the average salaries of data scientists. Let's
see what the internet has to say about this. The average salary of data scientists based on
PayScale, Indeed and Glassdoor can range anywhere from $92K AUD to $110K. I'd say this is quite
accurate based on my experience but I do think it's definitely on the higher end of that range.
And just to note this is just an average so given a person's experience you could earn
less or more than this number. Average income in Australia is about $60K. So the average of a
data scientist is nearly double. It's reasonable to hit that income level after a couple of years
as a data scientist but it's very unlikely that you're gonna hit that straight out of uni out of
uni. A better expectation for a graduate salary would be anywhere from $60K AUD to $90K AUD. It's
gonna vary incredibly based on what you bring to the table, on your degree level and the industry
that you're applying for. Banks will typically be on the higher spectrum of that range whereas
startups or smaller companies might be on the lower spectrum. I would advise against picking a
graduate job or any job for that matter solely on the basis of salary. The quality of your learning
experiences and the people you work with is far more important because at the end of the
day. That's what's going to keep you engaged in your data science job as you start your career in
data science it's worthwhile strategizing about what skills you need and picking
jobs accordingly because you need to remember that your career is a marathon and not a sprint.
Sometimes it can mean taking a pay cut so that you can do a more fulfilling job where you'll learn
a wide variety of skills which might actually pay dividends in the future as it makes you more
valuable in the market. Of course not everyone is in this situation but it's something to think
about. If you're enjoying the video so far then consider subscribing. I make weekly videos about
demystifying data science. Now let's talk about the peak earning potential of data scientists. As
you level up in your career as a data scientist you can expect your pay to grow with the number
of years of experience you have and also with your title. For example levelling up to a senior data
scientist can often increase your average pay to around $140K per annum and let's check out how
salary grows with experience by looking at this chart by Precision Sourcing* a recruitment firm
for analytics professional in Australia. You can clearly see that as you get more experience you
can expect to move up in salary levels you can also see that majority of grads are making up to
$80K a year and majority of data scientists with more than 10 years experience are earning
more than 200k a year. So the peak earning potential of data scientists is quite high.
That's it for today if you enjoyed it then hit the like button and I'll see you next time.