hello everyone Zoe's here with another
video and another guest today I'm gonna
interview Omid Karr who is a data
scientist in Swiss Re with many years
experiences if you want to know how to
be a data scientist you should watch this
video Hi Omid how are you thank you
for joining us today
hi Zoe no worries thank you my pleasure
thank you so Omid to start can you
please tell us a little bit about
yourself and your career journey please
yes of course so my name is Omid
obviously and my background I guess is
in mathematics applied mathematics and
computer science where I did my
bachelor's and master's studies back in
Iran and followed by a couple few years
of industry experience at the consultant
in analytics after that I moved on to
Australia to do my PhD  and my PhD
research was really focused on the
application of predictive modeling and
optimization optimization to engineering
field and after that I did a couple
years of postdoctoral research back in
academia and then I decided to move to
industry about 6 or 7 years ago and
since then I have been working as
a data professional or data scientist
working with many other many different
industries including manufacturing
engineering finance and banking and
insurance and retail energy and utility
and so on currently , 
I'm heading the advanced analytics
function of a large international
reinsurance company and basically
leading the whole function across the
Asia Pacific region that's true well
lots of great experiences that's amazing
good on you
thank you so my next question is do
you think the background is quite
crucial for someone who want to be a
data scientist like today like can you
please elaborate for us how far the
background is important for someone who
want to be a data scientist , do they have
to have a mathematic background or a
computer background or like someone has
chemistry background are they able to be
a data scientist okay
well honestly data science and
being a data scientist today really
reflects on a very very wide spectrum of
jobs and skills and employment
opportunities if you wish so when when
you asked me about being a data
scientist and the background I I guess
pretty much anyone you would be able to
find samples of pretty much anyone with
any background can do data stuff however
that being said I I think having the
background in some sort of analytical
field such as most most STEM related
fields of studies would definitely
benefit the the the person not only
accelerates their their achievements and
their going forward in the career but
also I think make it a little bit easier
to pick up on new things that's true
so I do believe having a relevant
background is help would help you I
honestly believe that but again that
doesn't mean that yeah because I would I
would regard data science as it is skill
more than anything else so it's the
skill then you can you can learn to pick
it up but to become a proper data
scientist as a career you might need
some fundamentals absolutely yes sure
yeah so other people from that kind of
like different background like not
stem categories,  I think they need to do a little
bit more kind of like hard working to
get to their true and true by the way
that again as I said so say we pick up
something completely irrelevant like
that social sciences okay so if you do
social sciences can you still do data
science
absolutely can but the difference is
that you might not be counted as a
hardcore data scientist at all the
computer science and mathematics but you
are rather a domain expecting that
social science who can all have the
literacy of data and analytics might not
be too advanced but still can pick up
data can analyze and can make use in
back in your domain of knowledge and
that still makes makes data science as
part of your skill set but probably not
your full career picture whereas we have
dedicated that scientist the whole
career picture, it's ll hard core
stuff that that evolves in data science
that's exactly right
perfect so how about online courses do
you think like these people who want to
be a data scientist with any background
do you think with online courses they
are able to achieve their goal okay
that's actually a great question that's
I've been asked  that kind of
questions quite quite a few times so far
and that's actually a good question the
short answer is yes our world is going
toward an open source equal opportunity
and hence everything and knowledge even
the whole knowledge base of the human is
becoming open source and becoming
available to everyone so yes the short
answer is yes in that sense of things
however I do a stronger recommend to
data science  aspirants to make
sure that maybe I wanna pick up online
learning or online courses the freely
available or maybe a few box and many
many other materials that make sure the
quality is there
and for that they need to obviously I
always suggest that pick up some some
mentors in the field make sure that you
get guidance on on is about the quality
of the courses and not only the quality
but also the relevance to what you want
to do so try to specialize rather than
go and everything with the data science
Theme in the middle you go and pick it up
not really decide what you want to do
decide this specialization and go and
get your learning in that so I guess
that will will make it better pathway
more more robust and more easier to
achieve what what you want to guess
that's perfect that was a great answer
so  how about a skill like
what the skill do you think is important
for these people to make sure like they
are able to be a data scientist is there
any specific software or any specific
knowledge that they have to have well I
got a I got a repeat statement from
before data science do cover a wide
spectrum of skills and knowledge so I
guess for that reason I'd say as you you
could you could deduce the skill sets
that are required the box is quite
actually varied and could be big however
if I want to just give a few fundamental
pieces I would definitely pick up the
basics in terms of the math and just
accent probability as as as a
fundamental piece that you need to have
so I don't necessarily say you go to
advanced in that but you might need to
depending on utilization later on but to
start with you need to have that basic
level of math including linear algebra
calculus and district mathematics and
statistics and probability so I don't I
honestly don't believe that anyone can
can go for in that
science career without actually having
that background so go and make sure that
you know the basics again don't go to
advance but you know the basics to start
and I understand the algorithms and then
the next bit is about the reality of
computer science if you wish so you need
to have understanding about data and
algorithms as fundamental blocks of this
skill set and data science itself but
also computer programming build will
take you far if you know computer
programming and whatever I do by means
of computer programming I don't mean you
are software developer , not really just
know how to script things out to just
just a popular language Python something
like that yeah we do again start from
basics and you grow there but also one
another tier of skills that you would
need that is usually unfortunately not
being highlighted enough my point of
view it is the soft skills so as a data
scientist soft skills is super important
although I know that in many other
fields it is the same but for the
sciences in particular it is it's very
important soft skills including
communication so you even if you are
hardcore
top top to your data science table and
you can't really communicate your
understand your knowledge communicate
the results communicate what you can do
with your models with your fancy models
it's not gonna worth that much to a
business so communication problem
solving so understanding that to be able
to have that critical thinking thinking
outside the box understanding the
problem and finally business acumen that
is super super important in terms of
because cuz you're not there so if you
are thinking about a career so if you're
doing this for fun then go and have fun
don't worry about it but if you want to
have a career out of this you want to be
paid to do what you love to do that's
really important for that people that
they wanna pay you that to be able to
get benefit from what you do so make
sure that whatever you do can translate
in a good way to business outcomes so
have that understanding from the domain
that you're working in and from what
Data is popular in there
what what sort of analytics what sort of
problems
what sort of metrics they're looking at
there to to measure the success so I
think that this kind of put all of these
on their soft skills and that's
absolutely a an important and is a
significant part of part of your skill
sets that you're going to need to to
become a successful data scientist
that's exactly that that was such a highlight
like I hear from a lot of people who are
like data analysts or they are kind of
like in computer field and they want to be
a data analyst or data scientist like
that's what they always says they're
like I'm already learned about R,Python
tableau power bi what else do you think
I have to learn and I'm like so how
about you soft skill like it's not
only about technical part,  don't be
focused on learning all software's on
the world there would be a new one soon
in the future and you wouldn't know how
to work on it is all about logic but
work on your soft skill which is very
important absolutely it is from whatever
you want to do there are multiple tools
available to be able to do the same
thing - really does it make you way
hotter in the market  to know five of those
tools or you really know your way around
and do anything you want with just one
of them so for example you mentioned
power bi and  tableau okay both of them
are great tools, both of them are great
for visualization but really wouldn't
take you too much too far if you know
both of them I'd rather have someone
that no back and forth tableau or the
other one and and do you know why why do
wanna do a visualization how to do a
visualization and even if without those
tools they can still provide good
visualization stories for me that is the
skill that I would need in a business
rather than the tools always make it a
little bit fancier but that's not all
about it right yeah that was such a highlight
thank you
so getting to this point , Omid
if you want to interview someone what is
the most important part for you like as
I've noticed now knowing more about
software and stuff is not that much
important for you so what really matters
for you to kind of like hire someone and
putting it in another word if someone has
kind of like some individual project but
not university qualification like
someone is very successful on freelanc
or on github so are they able to secure
the job like if you want to interview
such a person like that do you trust
them and give the job to them absolutely
absolutely so for me as a manager again
that doesn't mean that university
qualification is not good I still regard
it as good good start, so it doesn't mean
that our university graduates are
disappointed because they don't have git-
hup project there but I think I think in
that sense for me the artifacts that you
generate to be able to show what you can
do and what you know anything is good
whether you that is your University
assignment project and their working
team whether it's a project on github
whether you contribute it to an
open-source package somewhere on some
some github repo or bitbucket repo or
or you did freelance work so I guess for
me as a manager then again if I put
myself  in that situation I
would definitely need to see artifacts
of the person there to kind of represent
what they can do how they can think and
I would definitely need to see that's
that's that's important for me to see
yeah to see their personal touch on that
because unfortunately rightly or wrongly
there is a lot of copying and pasting
happening in the industry I do that by myself
yeah you have to you go and pick up
Google things and stack overflow yeah
absolutely that's all I use it on a
daily basis so that's no shame in that
but when you want to present yourself
and your your resume your profile as a
professional data
scientist then I need to be able to see
those type of artifacts and that
artifact yes could be though leverage
using your university degree fine if you
have that but if you don't have I don't
really care I'm not looking for a PhD or
or or as other specific University
degrees I do look for your artifacts what
you generate it where you generate it
value so that's from the type the point
of view of basically showcasing your
skills but also from from another from
the softest skills I might have been I
might be emphasizing it too much now but
again as a manager and that is that is
exactly what I , I'm currently
managing about team of 19 across the
region across  in several countries
now and it's I do really need to be able
to do my job I do really need to be able
to rely on them and to be able to rely
on them, means they need to have these
qualities which they need to know how to
do teamwork that's it and also how to do
their part to contribute to team so that
is super important for me to be able to
make sure that I can deliver the
projects by the deadline and to a good
quality and also I need to know that
they they can communicate to the
stakeholders they can manage the
stakeholders the stakeholders are not
all of them are data scientists so some
of them do not really have that depth in
the knowledge but you still need to get
their approval get their agreeing so how
would you do that
give me situation so that's why I think
a
good chunk of my interviews presently
involved the the type of soft skill
interview questions that give me a
situation where you and that situation
doesn't really need to be in a workplace
because you might be a data science
aspirant not really have that direct but
you have done these type of projects on
github you might have been part of a
team on Kagol  and learn how to do do team
work that would  that would do for
me but just show me just give me the
situation I want to know your thinking I
want to know how you resolve situation
negative  situation or how to how
you actually approach problems so those
are the type of things that I would
definitely seek to seek to know the
answer to in an interview with a
candidate that was great thank you so Omid
how is the demand of being a data
scientist job in Australia cool well I
think Australia could be a little bit
behind the more advanced countries like
United States probably or China in the
front of in that data front and
analytics front but we're absolutely
chasing and we are absolutely gaining
our momentum and the the numbers the
demand for data science and in general
data and analytics professional have
have grown rapidly during the past five
years I've got actually a nice stat 
here from a Deloitte report in 2018 and
where they they mentioned a growth of
about 2.4 percent per annum therefore
for the demand in data science market
and the numbers they forecasted by 2022
will be reach about 340 K 
employment opportunities actually in the
market so I guess that's that's
significant and I think yes that
is significant the promise is there
different role is there and let's face
it we are we all
are moving toward a smart world
digital smart world where pretty much
everything will be data data based data
related analytics ana AI are all
these fancy words that you keep hearing
and the absolute break fundamental break
for that would be data and if I think I
think even outside the career rules to
even survive as any career you need to
be data literate honestly I'm not
getting there but for more dedicated
people in data science I guess the
demand is absolutely promising and the
numbers are growing in terms of the the
value of the market if you wish
flowing through the market for pretty
much for all the industry some of them
are a little bit ahead some of them a
little bit behind but again overall
billions and billions of dollars or
bigger are being injected in industry
there so the promise is there I guess
that that's that's a great time for
people for data science aspirants to to
make sure that they can actually grab a
piece of pie they can get into the
industry that's amazing so then how
would be the kind of like working hours
and job environment and also like wages
working from home these days but in
general yeah well covid-19
situation aside cuz that's that's
absolutely an anomaly might not be in
the future but I would say I think if
the in terms of the type of the work
and work hours to your point it's
actually quite a varied arrangements
we've got in industry today we've
got full-time we've got from permanent
point of view we've got full-time
part-time and also we have got a lot of
contractor
opportunities as well on market as well
the the thing is that if we compare to
to the to the engineering I guess it's
the data science can be thick is a type
of thing that you can actually do
remotely and it's actually good with the
with the type of working from home
arrangements and fewer touch points
could could be necessary but again then
compared to something like software
development it's probably need more
touch one so I guess somewhere in
between a a computes the traditional of
computers software development and
full-on engineering so somewhere in
between I guess in terms of the touch
points and the level of  the
contract that you need in terms of the
wages the numbers of the dollars is what
a piece I guess is that again that the
numbers are quite promising I guess
depending really on the seniority level
and the specialization in today's
Australian market on a permanent role on
a full-time basis you might be able to
get something in between that seventy
all the way up to two hundred plus K for
annual salary on a permanent basis on a
full-time basis and on a contract basis
if you do contractor and it might be
anything some some work with something
between four hundred all the way up to
fifteen hundred daily salary basically
yeah so that's those are those are some
promising numbers again
compare you today I think I think in
terms of the writings are unfortunately
I don't have a reference here but I
think a study that I read the while
before in terms of the comparing the
industries and salaries the data
science overall is sitting in like a
third third or fourth tier in terms of
the the income level in our country yeah
totally by yeah exactly
just just before but just below medical
and more of the medical side of things
then in terms of the more engineering
and computer science I think I
think it said it's 
which is again quite promising yeah
that's true
perfect thank you very much Omid
is there any other you covered
everything and I'm sure it's gonna be
very useful but is there any other tip
or advice that you're gonna give to
those students who are going to be
graduate from university and looking for
the job and also those who emigrated
from all different countries to
Australia and they want to be a data
scientist is there any other tip or
advice for them ah yes actually I think
I might have by the way touched on some
of these before but I do still would
like to insist on a few of them so I
guess especially for more new comments
into into the market into the industry or
like fresh graduates or even migrants
that are now new to might have had years
of experience overseas but now new to
the market I do strongly recommend I
can't recommend this enough do get a
mentor a mentor can help you absolutely
significantly so and there are some
super super nice and friendly data
scientists in industry I know a lot of
them my colleagues my peers and they're
willing to actually help the fresh
graduates and I threw me through
universities there are mentorship
programs available and you can actually
be connected to two industrial
professionals but a mentor can again you
might be able to achieve things without
a mentor yes true but a mentor would
really keep you from wasting time and
kind of point you in the right direction
rather than go and try this and try this
and Fridays and error trial and error
will help you a little bit more more
optimized pathway toward what you want
to achieve that's right so I think
that's one one of the things so
mentorship one-to-one or even I do to
suggest go and be part of meetups there
are a lot of good meetups around start
your network there are a lot of leaders
in on LinkedIn you can follow can get
good material in a and good contact
content relevant content so that's the
first one the second one is one thing
that is has has been changing in the
industry in the data science world above
about seven eight years ago when I when
I started in industry maybe here in
Australia things were a little bit more
general what what does that mean it said
data science was mostly general field so
as a data scientist people would expect
you to know  learning to know deep
learning to know optimization to know
blah blah and blah so you had that you
had a big breath of thing you might have
not enough depth in certain things but
you had a breadth or two,  but had  the
breadth of knowledge so I think that has
has changed and it's being changing as
though so it's now we are moving toward
more specialized areas within data
science so that's something that I do
especially for our fresh graduates and
people looking at starting in this field
make sure that you find your interest
and passion within the field and find
what area is closest to that and then go
and specialize in that so you've got now
today we've got ML engineers we've got
ML ops we've got data engineers we've
got visualization experts and all these
different sort of things are all used to
be said data scientists so now that's
why and that's why I do recommend that
it will it will certainly help you with
the career and the pinpoint where you
need to grow your skills rather than
just go and learn anything 
 yes and finally
is I think never stop learning that will
that will be a pretty pretty much for
for everything I guess today in today's
world and the future
reflects every every other fields I
guess but the same for data science
never stop learning not not for as a
fresh graduate nor as a manager no as a
senior manager and all the way up so you
always need to learn you always there are
always new things and you're growing
you're rapidly in this field so at least
know your stuff know keep up with the
growth again you don't need to be
expert in everything , just know the
ideas to be able to relate with them so
yes that's absolutely in one one phrase
I would say never stop learning that is
that is that is my motto anyway yeah
yeah that's true that was very
inspirational thank you very much OMid
I really enjoyed and I'm sure everyone
was gonna watch this they're definitely
gonna enjoy as well
thank you I appreciate it Zoe from from
the time and I do I do love to actually
help help a fresh starters  in the field
I do mentor people as well myself and
whoever the audience of this video would
be feel free to follow me on LinkedIn
and get in touch with me I'm more than
happy to to give you hints and tips in
the bits and pieces about the industry
help you and mentor if you if you need
to at least just shed some light and
guide you in the right direction I'm I
don't know the answer to everything but
I have a big network of professions I
might be able to help you so more than
happy to help our next generation data
scientist I guess that's that's that's
I'm passionate about so really enjoyed
that chatting with you and thank you for
your invite again that's awesome
thank you so I provide your
LinkedIn link in the below as well for
everyone who's going to use it and be in touch with you in the future
thank you Zoe
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