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Kirill Eremenko: This is episode number 235 with Data Science
Consultant, Nic Ryan.
Kirill Eremenko: Welcome to the SuperDataScience Podcast. My name
is Kirill Eremenko, Data Science Coach and Lifestyle
Entrepreneur and each week we bring you inspiring
people and ideas to help you build your successful
career in data science. Thanks for being here today
and now let's make the complex simple.
Kirill Eremenko: Welcome back to the SuperDataScience Podcast, ladies
and gentlemen, and welcome to Australia. Today I've
got a data scientist who I'm talking with who's from my
home country, Australia. Nic Ryan lives literally 4
hours away from where I am right now in Bundaberg.
And on this podcast, we had quite a casual chat about
data science and his journey, his career. So what you
need to know about Nic is that he is a data scientist
but he's an external data scientist, like a consultant
that goes into businesses and does data science work
and at the same time, helps businesses with data
strategy, with how they can use data on different
projects, and things like that. So he does a mix of
things all relating to data. And actually he also does
mentoring of business employees to help them in data
science. And what I love about Nic is if you go to his
LinkedIn page you'll see him surfing some waves in his
background image and that's what he's all about. His
lifestyle is very relaxed, very laid back. He's built a life
for himself where he can do data science remotely and
occasionally go to visit his clients to help them out
onsite.
Kirill Eremenko: So in this podcast you'll learn how exactly he did that
and perhaps some tips that you can apply to your own
career to boost your success or maybe even build a
similar lifestyle of remote work in data science. We talk
about the whole notion of why data science is slowly
becoming more and more popular in terms of remote
work and also we talked about some of the projects
that he did. He shared a couple of examples and we
even talked about natural language processing, so
you'll hear some of those comments towards the end of
the podcast.
Kirill Eremenko: All in all, a very chilled, relaxed podcast so get ready to
explore the world of data science consulting and
working remotely.
Kirill Eremenko: Welcome to the SuperDataScience Podcast ladies and
gentleman. Super excited to have you back here on the
show and today we've got a very special guest, Nic
Ryan calling in all the way from Bundaberg,
Queensland, Australia. Nic, welcome to the show, how
are you going?
Nic Ryan: Very well, Kirill, and yourself?
Kirill Eremenko: Very well, too. It's exciting 'cause very rarely it
happens that not only we're in the same time zone but
we're actually in the same country and the same state.
We're like four hours away from each other right now.
Nic Ryan: Yeah, and Australia's a big country so you're
practically down the road. Four hours away.
Kirill Eremenko: That is crazy, yeah. That is so exciting. So you're on
the beach in Bundaberg. How cool is that? On a Friday
morning.
Nic Ryan: Yeah, still some work to do but no it's kind of been
interesting thing. I grew up in Sydney, well the central
coast of New South Wales, and bounced around
between Sydney and Melbourne for work but yeah
being able to get the lifestyle here in Bundaberg but
also traveling to still Sydney and Melbourne and
Brisbane for work is kind of good. It's kind of like the
best of both worlds.
Kirill Eremenko: That's awesome and I think that'll be a central topic
for today's podcast. The whole notion of doing data
science remotely, of working in data science for living
the dream, fulfilling the need to code and create stuff
and do analysis, but being able to work out of the
office. I love your comments about that it's actually
something that the world of development has already
started embracing and there's a lot of developers that
work remotely from home, and slowly data science is
moving towards that. So, I'm pretty pumped to talk
about this on this podcast episode.
Nic Ryan: Yeah, and you do with your business as well, having
that flexibility to ... you mentioned as well you spent
some time in Brisbane but you're also in other places
as well, and being able to move around and meet
people and see new things and being able to have a
real bird's eye view of the data science community and
what's happening in different cities is kind of cool.
Kirill Eremenko: Yeah. So, you guys listening to this, Nic mentioned at
the start before the podcast that he's got some
questions for me as well so I'm completely unprepared.
We'll see how this goes. It'll be fun.
Nic Ryan: It's a great opportunity to hit you up with questions
'cause as I said I'm a big fan of the work that you're
doing and the way that you've been able to
democratize the data science education to help people
out in their journey. I think it's just awesome. And so
yeah it's a great opportunity to-
Kirill Eremenko: Thanks man.
Nic Ryan: Find out what you guys are doing cause it's pretty
exciting.
Kirill Eremenko: Thanks, man. Thanks. Alright, well, we'll get to that
but to get us started, to kick things off, tell us a bit
about yourself. Where are you from and how did you
get into data science? I read a little bit about your
story and I think it's pretty exciting.
Nic Ryan: Yeah, yeah. I grew up about an hour and a half away
from Sydney, north of Sydney in between Sydney and
Newcastle in Australia and I guess at school I was
pretty good at math and I also played a lot of
basketball. And so I always wanted to play basketball
professionally. That was the dream, to go to the States
and play basketball.
Kirill Eremenko: How tall are you?
Nic Ryan: I'm 6 foot 1, I was nowhere near tall enough, but that's
one issue. But I wasn't good enough as well, Kirill,
that's the critical issue.
Kirill Eremenko: Oh.
Nic Ryan: You know like Muggsy Bogues he's like 5 foot 3 or
something and he's able to do it but I didn't have those
skills. Yeah that's a bit of a disappointment, bit of a
letdown, but my career advisor at school said "hey
there's this thing called actuarial studies and you can
do that at university" so um-
Kirill Eremenko: Very similar to basketball. Second thing behind
basketball. Next best option.
Nic Ryan: Well yeah, next best option and it's kind of funny as
well here because I still play basketball a couple times
a week, my dad still plays basketball actually.
Kirill Eremenko: Your daughters play basketball.
Nic Ryan: My daughters, my dad, the whole family, everyone
plays basketball. My dad's 63 he's still playing.
Kirill Eremenko: Wow.
Nic Ryan: Basketball. And I still play a couple times a week, but
yeah more for fun, but a lot of the guys here actually,
are playing at a high level. A couple of them have gone
over to college in the States which is pretty amazing
from a small place like this. But anyway, I digress.
Nic Ryan: I did actuarial studies and I ended up working for
insurance companies back in Sydney and Melbourne
and that was really in the early days where we started
to fiddle around with some aggression modelling and
we started to do some special smoothing and some
mapping and early fraud detection, and even some of
those sorts of models. And it was really the statistics
and what was data science machine learning that I
really got into but I didn't really know how to code. I
didn't really know programming, and that was my
weakness, and so I just worked on those skills, and
over time this institute just grew around me. So I
ended up working in banking building credit risk
models for banks, and doing some consulting to local
lenders in Australia, building their risk models that
were mainly regression-based models, over many
years. Then as well, working with some different start
ups and the natural thing was to then start my own
consulting business.
Nic Ryan: Where I fit in really is, all of the companies they'll have
their senior leaders and they'll have their staff but I fit
in as a technical manager there, compared to someone
like a Deloitte or KPMG the rates I charge are very
reasonable and it's something that ... the companies
that have say 20, 50 people, and they're interested in
AI, they may not be able to afford some of those other
guys but where I come in-
Kirill Eremenko: Gotcha. So you found your own niche.
Nic Ryan: Yeah, yeah, it rolls off the tongue, but that took a
couple years of trying.
Kirill Eremenko: That's actually what I wanted to dig in. First of all, you
totally skipped the exciting part about the two hour
train ride and how you fell into data science. Tell us a
bit about that and then I have another question for
you.
Nic Ryan: Yeah, that's right. So that actually does take me back.
Sometimes you brush over the more painful parts of
your life, kind of keep them in the back of your
memory there. But, yeah, I was pretty young, I had the
kids, and so I was on the last part of my actuarial
exams and I knew that actuarial wasn't for me. I just
knew it wasn't something that I was really passionate
about, and I think-
Kirill Eremenko: What is actuarial for the sake of those that might not
be familiar with this profession?
Nic Ryan: Yeah, it's more about predicted modelling and maps
and stats for insurance companies, really. So to
predict [inaudible 00:10:04] Some that they're
reserving to be able to predict when clients are going to
occur and how much they need to put aside and some
of it as well is around pricing of insurance products,
as well. But they're kind of like the people that do the
math and stats for insurance companies.
Kirill Eremenko: Yeah and what I like about actuarial is the whole ...
they deal with demographics and population statistics
and how long are people in this age group, what
happens when they transition to retirement? There's a
bit of this whole human or social component to it.
That's what makes it a bit of a different profession
than just pure plain statistics that you're just dealing
with numbers and mathematical equations.
Nic Ryan: That's right, yeah. And there is a certain matter to
main expertise that you have to know in any field like
that and especially in insurance, yeah, you need to
know, be down with some of those. And things about
the different policy rules, the different insurance
products as well, so yeah it was interesting. A lot of it
as well, even back in those days, I think it was a lot of
spread sheet work and so it almost felt at times like
glorified accounting. Not that there's anything wrong
with that but it was ... it certainly has changed now
where there are data science professionals attached to
actuarial teams and they're doing some really cool
stuff. But for me at that time it wasn't something I was
super passionate about.
Kirill Eremenko: Yeah.
Nic Ryan: So, to each to their own. So then I was moved over to
banking and I did get really passionate about building
risk models for banking which is weird, but I really
thought it was pretty cool. And so I had a pretty long
commute from on train, we're talking close to a couple
hours each way, door to door.
Kirill Eremenko: Wow.
Nic Ryan: Each day. So yeah, 4 hours. Four hours where you're
not around seeing your family and seeing the kids and
everything, so I was stuck on the train and I thought
well I can either get sleep or I can use this time
productively. So there's probably about 2 and a half
hours a day which I had to study and it was the early
time of Coursera, and they had some of the moocs out
there and I started learning the programming language
and did some of the courses through John Hopkins
University, like Jeff Lake, and those guys. And also,
the machine learning course [inaudible 00:12:30] and
just a few others, and I thought "wow this is special.
I'm really enjoying this." I really had a passion for it.
Nic Ryan: And so, within a few years, I got a phone call to move
to the Gold Coast and to essentially head up data
science for a start up there. And so the time from
learning to something significant happening was pretty
short-
Kirill Eremenko: Interesting. Out of curiosity, you weren't actually ...
people don't find you through learning unless you put
yourself out there. Did this happen through your
Linkedin page? Did this happen through something
that you shared? Did this happen through a
connection? How did that phone call happen?
Nic Ryan: Yeah, I wrote a pretty early blog, it's just a recruiter
happened to stumble upon it and I really think that
putting yourself out there, it is scary but it's definitely
something you need to do. And it's absolutely essential
for my business to be out there, 'cause that's how
people find me. I mean you can knock on doors and
you can try to say what you can do but showing what
you can do and having people come to you is usually a
better equation.
Nic Ryan: And so that's what happened. They were looking for a
head of data science and they looked for 4 years and
they couldn't find someone. They had pretty simple
criteria. They wanted someone who could do the
technical work and someone who could also talk a bit,
and it's really hard for them to find both. And so, it's
extremely hard to hire people that can't communicate
as well as doing the work. And they even tried as far
away as the U.S. and other places as well and so when
the recruiter said "there's a guy in Sydney who you
might want to have a chat to" and then I had a plane
ticket and off I was. And you're on the Gold Coast now,
it's a great place to live-
Kirill Eremenko: Yeah, fantastic place. It's a dream place. It's called the
Gold Coast for a reason.
Nic Ryan: That's right. Where you are now, Southport is where I
was living as well, so I would go for a surf before work
and then go into the office. I'd skateboard into the
office. I'd commute by skateboard, so yeah not very
professional showing up with a skateboard under your
arm but there you go.
Kirill Eremenko: Yeah. That's pretty cool. That's pretty cool. Actually,
yesterday I was walking on a bridge in Gold Coast and
this guy in a not too formally dressed, but in a shirt,
looking smart, on a skateboard, probably your protégé.
Nic Ryan: That's right.
Kirill Eremenko: Taking off to work.
Nic Ryan: My little brother's actually a lawyer and he actually
works with my dad who's also a lawyer and my dad
was driving to work and my brother's really keen on
electric skateboards, so he's weaving in and out of
traffic on an electric skateboard and my father thought
"who's this idiot weaving in and out of traffic. Oh, it's
my son."
Kirill Eremenko: Oh, that's too funny. Okay, gotcha. So, that's a great
comment. Even before you started your business ... I
completely agree, when you have your own business
it's important to put yourself out there so people can
find you and connect with you and know that you can
help them out. But even before you started your
business, putting yourself out there, writing that blog
post was an important way to put your foot in the door
and actually for that recruiter, it showed them that
you're a person who can potentially communicate and
maybe take on this role. So just for those listening out
there, it's a great note to take. It never hurts. It is
scary to put yourself out there and share some of your
thoughts or learnings but it never hurts. What harm
can it do? It can only lead to good things, right?
Otherwise you would've never gotten this phone call,
never moved to the Gold Coast.
Nic Ryan: Yeah, that's right. And for you. How did you get
started? In a similar way, also putting yourself out.
'Cause for you, you were working for Deloitte and you
were doing some consulting work and then I'm just
curious about how you got into doing the courses-
Kirill Eremenko: Good question. Here come the questions.
Nic Ryan: Sorry.
Kirill Eremenko: No we're good. For me, I worked at Deloitte for 2 years
and, amazing company. I couldn't recommend higher,
the professionalism and excitement you experience
when you're at Deloitte, different types of projects. But
if there comes a time when you ... life changes or you
feel that you want to move to the next level or
something else is exciting ... for me, that was after 2
years I felt that "alright I've had enough of all of this." I
worked on probably a dozen or more different industry
projects, learned so much, and grew very fast, and
then I kind of hit a ceiling in terms of my growth, and I
decided "alright I want to do something of my own. "
Kirill Eremenko: And from there I started searching for different
options. How can I start a business or how can I
become ... make money in a passive way, or how can I
help people do certain things that I'm passionate
about? And stuff like that. And one thing led to
another. I started putting out courses on things I
knew. And at the time, I knew really well a lot about
forex market and how it works and financial
instruments and stuff like that, so I started putting
out courses on that topic. And again, similar to you,
because I started putting myself out there, found this
platform, Udemy, which I found completely randomly
through an eBook that I was reading about another
instructor who's course I was taking. Anyway I started
putting out these courses. And that went well. It
turned out that I'm pretty good explaining complex
things in simple ways and Udemy themselves reached
out to me and said "hey what else do you know?"
Nic Ryan: Yeah.
Kirill Eremenko: And I said "data science" and they said "oh how about
you create some course on data science," and that's
how it all started. But similar to your story, had I not
started, had I not gone through that painful, fearful
exercise of releasing my first course on writing
algorithms for trading stocks, not stocks, currencies. If
you listen to that course now you can hear how shy
and how timid I am. I'm nervous, almost panicking on
the microphone. But had I not done that, had I not
pushed myself through that experience, then that
would've never led to that, as you say, phone call. For
me, it was an email from Udemy saying "hey man, let's
do some more stuff." And from there, turns out that
data science is something that people need. Lots of
people have, since then, have been able to learn from
the courses that I've created. I'm really excited mostly
about that part. That, that's where it all led.
Nic Ryan: Yeah, I think as well with what you guys are doing
now, you've got the SuperDataScience Platform the
2.0, that you're doing, and so that's access to all your
courses, and for what is I think a pretty normal figure,
about 150 bucks a year as well so it almost feels like
you're graduating again from Udemy in a way.
Kirill Eremenko: Yeah, yeah.
Nic Ryan: You've got something pretty exciting there, too.
Kirill Eremenko: You always got to grow and develop right? I find in life,
every new experience is like a step, and then you learn
and you're like okay, cool, that's great but as soon as
you feel there's something more, some new way you
can go, that's really cool, and thanks for mentioning
the SuperDataScience 2.0 which we just launched.
Nic Ryan: Yeah.
Kirill Eremenko: Very very excited about that. By the way I wanted to
ask you. How did you find out about
SuperDataScience and things that we do?
Nic Ryan: No, I mean, yeah through Linkedin. Linkedin's actually
been a good way to ... for me, I'm quite isolated here.
There's no other data scientists around. It's really just
me in the area, and so I probably have to drive down
the road to where you are to find someone else to talk
to. With social media, with Linkedin, with even Twitter,
with those sorts of things, you can really be connected
to the industry wherever you are. And so, just keeping
tabs on what's happening. I've done a couple of your
courses as well, and I really love them as well.
Kirill Eremenko: Thank you.
Nic Ryan: And in particular, the AI course as well-
Kirill Eremenko: Which one? I think we have five of them.
Nic Ryan: Put me on the spot, I don't remember, but it's the one
with Hadelin and he does ... I can't remember what it's
called. AI or something like that.
Kirill Eremenko: Is is the recent one or is it AI, artificial intelligence A to
Z, or is AI for business?
Nic Ryan: It's an A to Z one.
Kirill Eremenko: It is. Oh, okay. The fundamental one.
Nic Ryan: Yeah, the fundamentals. But what I liked about even
those courses as well is that some of the ... if you look
at YouTube tutorials, you're kind of passively coding
and you just kind of look up and code some more, look
up and code some more, but with what you and
Hadelin did is you're like oh okay, here are there
papers. Go off and read some of these papers.
Kirill Eremenko: Yeah.
Nic Ryan: Or, here's something else. And it's kind of like it's
putting the ball back in the court of the student to
take responsibility for their own learning as well, and
you're kind of acting more as a guide rather than just
telling them "hey do this, hey do that."
Kirill Eremenko: Yeah.
Nic Ryan: So, that's pretty cool. And some of the other courses
going that way as well-
Kirill Eremenko: That's awesome. And what we ... I don't want to make
this podcast a promotion of SuperDataScience 2.0 but
I think its important to mention that what we aim to
do with this new platform, that's why we've been
developing it for two years actually.
Nic Ryan: Wow.
Kirill Eremenko: Yeah, it's been a while. But the main thing here is and
it's constantly in development, constantly improving,
but one of the things that we're releasing very soon is
the gamification component, where not only do you
take the course and as you said you have exercises or
you have papers to read and things like that, but
actually as you progress through a course, you get
certain badges, and unlock achievements, and get
points, and that's ... even though it might sound very
childish or not for adults and things like that, but
actually it is very cool to see your own progress and
feel like oh that's awesome. I unlocked this level in my
education. And the goal of that is not to turn it into a
game but to actually help people get into it, motivate
them.
Kirill Eremenko: How many times have ... I've done this plenty of times.
I sign up for a course and I don't actually, I take one
tutorial, or I don't even look at it or anything like that.
So, but if somebody helped me get into it, somebody
helped me get started and get momentum and I
realized how powerful this is for my career and for my
personal growth, then I would continue going. And so
that's one of our main missions now is how to actually
help people select the right career paths and courses
for those career paths, but then actually motivate and
inspire people to keep with education. Stick to it and
hold themselves accountable to it.
Nic Ryan: Yeah, and I think as well, for anyone, well anyone
that's listening and if they are taking some
responsibility for their own education, if they are
trying to learn new things, immediately that puts them
in the top small percentage of people out there.
Kirill Eremenko: Yeah.
Nic Ryan: Most people, and I've known this from managing teams
and that sort of thing, but very small percentage of
people, whether they're software developers or data
scientists will learn outside the job. They tend to ... a
lot of people, their learning is their 9 to 5 job and they
don't want to do anything outside. So, if someone is
actually taking that initiative to sign up for courses
and to do it, they're already ahead of the game. And
that's the thing as well, when I used to hire people, it's
just is this person as passionate as I am? I'm working
with a guy over in London, really nice guy actually.
Martin Paver. His company's called Projecting Success
and it's a start up and he's applying AI and machine
learning to project management data analytics, so
really quite exciting. Really quite changing the project
management space. But, I was speaking to him a while
ago and he said words to the same effect, that when
he's looking at hiring people, whether interns or more
senior people, he's looking for evidence of that passion.
And so he's looking for ... you could get someone and
they could've spent 100,000 US dollars on their
education, which is fine, but it's really are they going
to hackathons, are they looking at moocs and doing
online courses? What's the evidence that I can see that
this person is passionate about the field?
Nic Ryan: So, for me as well, even if they don't have a high school
education, that's kind of irrelevant if they're super
passionate about the field, because anyone with that
passion and that drive and if you guys are helping
them to get that passion and drive and keep them on
track like anyone can do this stuff. And they just gotta
be pumped about it.
Kirill Eremenko: Yeah, totally agree. That's very valuable. For those who
were at DataScienceGO last year, Ben Taylor actually
talked about that, that companies want to hire people
who are somewhere between passion and obsession
about a topic. You gotta be passionate or even maybe
obsessed to certain extent, and then it's a no-brainer.
Companies will want you on their teams.
Kirill Eremenko: Alright so that's a quick digression there.
Nic Ryan: That's right.
Kirill Eremenko: Side route. I wanted to rewind back and this is the
second question I wanted to ask you. So you told us
about the train ride and how you put that to use,
which I think is very inspiring. Tell us the other thing
that you said was "it was a natural step to start my
own business." It might seem natural for you looking
back, but trust me, it's not a natural step to start your
own business. The way I remember it, it was a lot of
trial and error, a lot of fear, a lot of "how do I do this?
Will I succeed? Will I not?" So, how did that all
happen? You moved to the Gold Coast, you were
working there. Walk us through how you went from
that point in your life to actually becoming a
consultant and working for yourself, working remotely.
Nic Ryan: Well again, I guess you don't know the history, so my
wife's mother moved to this area, Bundaberg, like 18
years ago, so they've been here for a long time. I
always thought this was a nice place to retire and
eventually die. And so, I thought my ashes would be
scattered on that beach or something it'd be nice. So I
was-
Kirill Eremenko: Long term planning.
Nic Ryan: Long term planning, yeah that's right. It was always
gonna be here. So we had been holding here for a bit
and we really liked the area and it's nice and in terms
of weather it's the same as Hawaii, like all year round,
it's just awesome. And so, people here are very
friendly, and really nice.
Nic Ryan: I was working for that company on the Gold Coast and
I was managing a team that was based in Kiev and
also got to go to Kiev, which is a lovely place in
Ukraine. It was fantastic. And also a team on the Gold
Coast as well and just pushing a bit hard because
there was a bit of pressure in that job I will say. And,
responsible for a lot of people. So at the expense, I
didn't get the balance right, you know I didn't get the
balance between family and work and life right. So it
was not great. So I didn't see my kids all that much
and I was almost going back to when I was catching
that train and commuting long hours to Sydney. So I
thought well, something has to change here, because
my kids, and it's actually probably an important point
for people as well, your colleagues and stuff are good
and you should be nice to your colleagues, but really
your family and your kids are critical, because in 5
years time they may or may not ... you know your
colleagues may or may not remember you but in 80
years time, your kids will.
Nic Ryan: And so it's really important to get that balance
between family and work right. And so my wife, we
went camping in the middle of nowhere, about 3 hours
west, in the middle of Australia and then she just said
right "we're moving here." Cause I was relaxed, we're
looking at the campfire and she said "we're going to
live in Bundaberg," and I said "well there's no work
there," and she said "well tough you'll find some." So
that was it. And so she picked a house that she liked,
she bought it and that was it.
Nic Ryan: So, I kind of had to, and that was pretty good
motivation as well. And I always managed change. I
always liked mentoring junior data scientists and it
was a natural thing to be able to manage up as well as
manage down to some of the junior data scientists and
it is something that I really enjoy. In the same way I
enjoy taking some of the kids around here for
basketball and coaching them and within 2 years,
some of them are playing representative basketball. I
think "wow, that's kind of cool to see." So, I've always
liked that, always liked taking someone who's fairly
green, a novice and being able to help them out on
their path, whether it's basketball or even data
science. So it seemed like pretty natural thing to do.
Kirill Eremenko: Gotcha. So, very interesting and very ... overnight
transition almost, and would've been challenging but
at the same time exciting to make it all work. Tell us a
bit about remote work. So, you moved to Bundaberg.
How do you find your clients? Or how did you find
your clients at the start? How did you set up this
whole system for yourself where you on one hand are
relaxed and at home, but at the same time you do
have a stream of work coming in?
Nic Ryan: Yeah, I mean I was getting paid pretty well when I was
working in the city so I did have a bit of money which I
could go on for a while. So it wasn't that immediate
pressure to find the next dollar. Also, not having a
mortgage or anything like that. You can live pretty
cheap here and we've got a fairly big lock of land, you
know 7 chickens and grow our own fruit and
vegetables, so my expenses really are quite minimal.
Kirill Eremenko: Okay, gotcha.
Nic Ryan: So I didn't really need much money to be honest. It
was only just my expenses are pretty low. So I could've
kept going for a bit while. But what I was doing
actually before then was just writing, 'cause I was ...
well, to start off with there was a little start up
company in Melbourne that I was working for and so
that was good. I just started writing about some of the
things which I wish I'd learned when I was learning
data science or some of the things I was seeing or just
some of the thoughts, because if you can picture it, I'm
in a room by myself writing code, so it's a little bit
isolating, but Linkedin as well has really helped to
build that community.
Nic Ryan: Eventually people started approaching me for different
ad hoc tasks and some for even longer engagements,
so I typically might do a few hours here, a few hours
there for different people, and there's actually a really
great AI consulting company that's based in Brisbane
called Blackbook AI and Thuy Lam, he's a friend. He's
a really nice guy but he reached out to me. He'll just
book a plane ticket for me and say hey Nic, we need
you this day, and I'll be flying into Brisbane. Working
with them is wonderful and they've got a great mix of
junior and senior people and so being able to mentor
and help out those guys is just awesome.
Kirill Eremenko: Oh okay, gotcha.
Nic Ryan: And so that's the ... and also help them on projects
when they need it and a combination of meeting
clients and also doing some of the data science work is
kind of cool. And so it really is a mixed bag of stuff
that I do, and it keeps it really interesting.
Kirill Eremenko: Very cool. Okay, so you not only do the data science
work but you actually help them build teams, help
them get their staff on track and consult the
executives and things like that. So I think that's a very
exciting space to be in, especially now with the boom
in data science and artificial intelligence.
Nic Ryan: Yeah, and I'm pretty picky about the people I work
with. I think you have to be and you have to be in it for
that long term relationship and so those two places
that I mentioned, Projecting Success over in London
and Blackbook AI in Brisbane, just great people. Just
great people to work with. And so, you do have to be
selective and kind of in it for the long term. It's also a
bit more of a pipeline and there's some really cool
people that I've met in Melbourne last week and also
on the Gold Coast as well, this other little start up
company. Some of these things still in the pipeline, but
yeah, they seem like really good people as well so it's
cool. It's excellent working with great people.
Kirill Eremenko: Awesome, awesome. So, tell us a bit about projects.
You mentioned that you've been doing quite a lot of
different ... working on a lot of different projects,
different companies. Are there any case studies that
you can share with us of recent work that you've done
without disclosing clients, or disclosing any sensitive
information, just for the sake of maybe what kind of
tools you did or used or what kind of changes you
helped the client implement in terms of their staffing,
in terms of their strategy, and whatever else that you
were working on recently?
Nic Ryan: Yeah I think the one that's really quite ... there's a few
and obviously I'm going to be careful about talking
about it too much, but what I think is really quite
incredible that Projecting Success over in London are
trying to do, is essentially, they're trying to build a
credit bureau, something like a credit bureau but for
project management. 'Cause what they've seen is a
whole heap of different companies and different
industries are doing different projects and they're not
necessarily learning lessons from those projects so
they're repeating the same mistakes. So what you've
got is a whole bunch of spreadsheets and emails and
word documents to manage projects. And so they're
about digitizing that information and storing it in
databases and eventually all companies pooling their
data collectively to be able to ... so say I'm an
agriculture company and I'm doing an IT
Infrastructure change. Well maybe I can learn some
lessons from another IT Infrastructure change by some
other company maybe doing manufacturing or doing
something different, but it's still an IT project.
Nic Ryan: And so what they're looking at doing is building really
cool databases to collect that information. And to work
out multiple parts and that sort of thing for projects to
keep them on track and to minimize spend and to
minimize the chance of it going around over time with
no budget, which is a really inspiring kind of thing. So
there's one that completely changed that project
management space, which is cool thing to be a part of.
Kirill Eremenko: Very cool. And so what's your role in all of that?
Nic Ryan: So, for me, I'm helping out with ... well they have a
combination of interns and they have also a CTO who I
help out as well, and even Martin who's the founder,
just helping him with strategy and advise as well, so
it's everything from meetings with web developer and
seeing the different states of progress of the
applications through to ... yeah just different strategy
and advise-
Kirill Eremenko: Interesting. So you're not, in that specific situation,
you're not doing any data science work per se. You're
not bringing to life any models, running any logistics
or other types of regressions, doing data cleaning.
You're actually acting as a data strategy consultant or
helping them understand how data can be used and
applied in the tools that they're creating. Is that about
right?
Nic Ryan: Yeah, for that project. I mean they do other things as
well where they've got a really good ... companies may
try for a ... [inaudible 00:37:39] They built a tool which
is again a machine learning model which predicts the
chance that someone's gonna win and how much and
what position they're gonna get in that particular bid.
So, and that's more hands on stuff that I've done.
Kirill Eremenko: Yeah.
Nic Ryan: So, again, it's a mixed bag of different work.
Kirill Eremenko: Okay, gotcha.
Nic Ryan: Yeah, and even with Blackbook, even. Yesterday
actually I had all the tools and again, bit of a pipeline
script that they're just going to plug into production
for a tool that they're creating, so again, I keep it-
Kirill Eremenko: It varies.
Nic Ryan: Yeah, it's good seeing different things. It means that
you're always learning as well, and so the imposter
syndrome is very real. People will often ask, some of
the junior data scientists will say "oh I don't know how
to do this." I'm like "oh just Google it," that's what I
say. It's hard. You've probably found that as well when
you started as well. You were thinking "oh, do I know
enough? Am I good enough?" And all that sort of thing.
Kirill Eremenko: Yeah. I heard recently that this question: "Am I good
enough?" Or that "I'm not good enough" is the most
frequently asked question in the world that people ask
themselves. And it's the cause of the most misery in
the world as well that people think they're not good
enough and therefore they're going to spiral into
depression or they don't go for opportunities. They
think ... that actually could change their lives or they
don't go up to the love of their life ... to meet the
person that might become the love of their life, and
things like that, so yeah, definitely I've asked that
question a million times. For sure.
Nic Ryan: Just one of my questions. I'm gonna shoot the
questions at you now. What do you do for fun? Like I
do a combination of basketball and surfing and
skateboarding but what do yo do for fun? Do you have
something that you-
Kirill Eremenko: Oh man, good question. I like sports. I notice this
about myself that ... I was talking about with one of
my colleagues at work recently and he likes what are
they called? Going to a museum and looking at
paintings and things, so something more for the soul. I
like those things as well. I like listening to a classical
music concert or going to a museum, but if I had the
choice I always go for experiences. I go for, like
recently, last week I went rafting with my dad who's
also in his 60s. He's 66. We went rafting in New
Zealand and we dropped down a 6 meter waterfall.
That was really cool. I like scuba diving. Monday this
week I went for scuba diving in Byron Bay.
Nic Ryan: Oh.
Kirill Eremenko: Yeah, like one of my top 5 scuba dives ever, so you
know ... I saw a bird under water.
Nic Ryan: What?
Kirill Eremenko: I saw a bird under water. It was like the last thing I
expect to see, one of those birds, you know how when
you see a bird from the surface then it ducks to go do
something?
Nic Ryan: Oh, yeah yeah yeah.
Kirill Eremenko: And you never know what they're doing. I actually saw
it doing its thing. It was swimming around, it was like
40 seconds underwater, went to this rock, looked
under that rock, then went and chased this fish, went
back up, got some air, came back down. Ridiculous,
man.
Nic Ryan: That's incredible. Yeah, that's something I mean to do
is go scuba diving cause even on my street there's
world class dive spot that you can go scuba diving. I
haven't been. I've been here two years. I still haven't
gone there.
Kirill Eremenko: Man you should do totally do it. It's like a whole
different world under the surface of the ocean.
Nic Ryan: Yeah, I mean you've probably done the scuba diving
course or-
Kirill Eremenko: Yeah, yeah, yeah. You gotta, if you want to establish
yourself you gotta do the PADI or some other
certification like the open water advanced, and other
levels that you might want. But it's fun. I like
experiences basically. I like sports as well but
something new, something where that's physically
challenging and that you feel engaged in and then
after it you're like "wow that was so cool." Those types
of things.
Nic Ryan: What sports do you play?
Kirill Eremenko: Oh, good question. This is a get to know Kirill podcast.
Nic Ryan: No no, sorry. I'm just-
Kirill Eremenko: Sports, well, what do I play right now? There was
something that I did ... oh I was doing Brazilian Jiu
Jitsu recently but before that I really like Taekwondo. I
did Taekwondo for 9 years, so martial arts mostly, and
I don't know it's kind of like the challenge, that
adrenaline that you get and yeah. And the whole
concept of getting better and learning new techniques,
so I would say martial arts.
Nic Ryan: Yeah, awesome. Yeah it's something that both my
daughters do as well is Taekwondo and my wife
actually represented the state in Shotokan.
Kirill Eremenko: Wow
Nic Ryan: Yeah, I can't do anything.
Kirill Eremenko: Wow, man.
Nic Ryan: Everyone in my house can beat me up.
Kirill Eremenko: Oh wow that's crazy. That's so cool. I heard Shotokan,
that's karate right?
Nic Ryan: Yeah, it's a karate.
Kirill Eremenko: Pretty brutal type of karate.
Nic Ryan: Yeah, yeah, she can defend herself pretty well.
Kirill Eremenko: Awesome, man. Alright well let's jump back in. What
were we-
Nic Ryan: Sorry, got you off track.
Kirill Eremenko: All good, all good. We were talking about how ... oh
this is what I was gonna say. You wrote, and I really
like this comment that you made in the notes for this
podcast, that you think data science leaders should
remain on the tools maybe floating in between projects
as needed, and then you continued "if you take your
best data scientist and make them a manager, you
probably end up upsetting them if they don't have real
work to do." And it sounds like that's what you're
doing. You're floating between helping companies with
their strategies and tactics around data, what they can
do, and mentoring people, but at the same time you're
not losing your grip on the actual applied data science
where you get to code things in python or r and create
things in regression models and what not.
Nic Ryan: Yeah.
Kirill Eremenko: What are your suggestions in general to people? How
do you maintain that balance of the two?
Nic Ryan: I think, looking back in retrospect, when I was in
charge of a fairly big team, and a lot of what I did was
meetings, and admin and approving sick leave, and all
that sort of stuff, and that's ... I don't know, I kind of
like you, you really enjoy the work. If you are
passionate about it, you do love the work and anything
that's gonna take you further away from that work
completely isn't great and so you ... I think as well,
sometimes a lot of people, they seem to want to
become a manager just because it means more money
and I think that's the wrong way to reward people
'cause a highly skilled technical person I feel should
get paid just as much as a manager because this is
something they've invested in. They've invested in
themselves.
Nic Ryan: For me as well to be able to relate to what a starting
data scientist is doing, it's really important to keep on
the tools and even in my spare time to be looking at
what's coming up and what's out there. Actually that's
something true for you as well. How do you keep up
with the industry? Cause it seems to be hard work just
keeping up with what's coming up.
Kirill Eremenko: Yeah.
Nic Ryan: But I think as well if you're on the tools you've got a
better chance of doing that.
Kirill Eremenko: Yeah man, totally agree. But for me, I have the luxury
of ... the content that I create, the courses, I have to
still relate it to the technical stuff. If anything I'm not
getting enough practical applications of data science,
like solving industry problems with existing data
science tool. But if anything when Hadelin and I are
creating courses, we're pushing the boundaries of data
science.
Nic Ryan: Oh, yeah.
Kirill Eremenko: We're looking at the most advanced tools. But I agree
with you. I would love to be able to do more commonly
accepted python or r models that currently dominate
the world rather than just only focusing on the ones
that are on the fringe that will become the dominating
ones in a year or two. But you know, as you said,
there's always ... you can't have everything, right? You
gotta balance it out.
Nic Ryan: No, I meant with ... obviously your courses you're quite
technical but I mean there's just so much technical
content that's coming out. It's really hard to keep up.
But I mean, you guys are massively on the tools and
the way you decompose quite important and difficult
concepts down for people shows that you are really on
the tools and you're really into the nitty gritty of the
content which is incredible. But just the amount of
stuff that's coming out, I think it is good for me to be
across different teams and different cities doing
different things to be able to see some of the
commonality between what people are working on,
what they're concerned with. And even just for some
reason right now there's a whole heap of natural
language processing tasks that are happening all over
the place and that wasn't the case even a couple of
years ago, so it is kind of good to see that. But then
there's so many libraries and the tooling for data
science is just getting better and better all the time, so
it's often a question of working out what's out there.
Nic Ryan: Even just yesterday I was working on trying to find a
way to detect emotion from text, whether someone is
angry, upset, disappointed, whatever, and I was
thinking "how do you do that? Is there some machine
learning API from google or" ... then all of sudden
there's this little odd library that we're doing. I just
think far out, it's hard to know. You pretty much have
to read the internet sometimes to find out all these
different things that are out there. There's a lot out
there and so it's almost a job just keeping up, I think.
Kirill Eremenko: Yeah, no I totally agree. I actually read your post on
Linkedin about natural language processing and it's
interesting how you mention that a lot of companies
still talk about structured data but around 80 to 90
percent of the world's data is in unstructured format,
and I agree with you, it's so much media. There's so
much video, there's so much audio, there's so much
people writing stuff, like texts, blog posts. How often
do we actually deal with structured data as humans?
Not that often. Not compared to how much
unstructured ... like we're talking right now, people
listening to this podcast, that's all unstructured data,
so it's important for data scientists to know how to
process things like natural language.
Nic Ryan: Yeah, even in applications like credit based lending. I
used to find it extraordinary that a lot of the banks
and lenders were sitting on transactional data from
bank statements and they didn't incorporate those into
credit risk models and so that's a gold mine to unset
and that's something that I did and I was working for
the on star company on the Gold Coast, was building
natural language processing for bank statement data
which was incredible. Incredibly rich data source for
lending.
Kirill Eremenko: Interesting. Very interesting. Tell us a bit more about
that. You obviously have a lot of experience with
natural language processing. What are some of your
tips or maybe some of the tools that you use and
maybe some of the mistakes that you've made that you
can help other people avoid?
Nic Ryan: Yeah, plenty of mistakes. I think often people will try
to, not just with natural language processing, but with
any kind of task, if you saw before we started, you can
tell by my haircut and my t-shirt that I'm a pretty
simple guy. So I usually like to start very simply. And
in a natural language processing task it is about
cleaning the corpus. It is about making everything,
just the basics, everything lower case, stop words,
looking at frequently occurring words, looking at
infrequently occurring words, you know stripping out
any numerics, and just cleaning the corpus and then
really eyeballing the data. Even just some of the plots,
some of the word cut outs, and some of the things
could be inside of what you're going to be looking at as
well.
Nic Ryan: And so initially when I start, I'll go for a pretty simple
bi-gram or tri-gram, which is just 2 and 3 word
features of words just to create context. So if you're
talking bi-grams, you might have say ... you know that
coffee shop is usually the example I give called Gloria
Jean's. If you're looking at uni-grams or single words
then you'd say, any time you'd hear jeans you'd go off
to fashion-
Kirill Eremenko: No.
Nic Ryan: Whereas Gloria Jean's is coffee shop, Gloria Jean's. So
having those two words as a feature in the model is
gonna be important to give you that context and even
three words sometimes for different company names or
whatever.
Nic Ryan: And so, I would also just try with a simple regression
model. So something like a multi class logistic
regression model would be the very first thing that I'd
try would be the very simplest thing. And to see how
that goes and then if anything, that forms a baseline
that you can then use to improve with better models.
And in anything I do, I'll always start off with a fairly
simple baseline and then in track and develop on that.
But getting the end to end pipeline and getting
something going is more important than getting
something optimal. And you were the same as well. If
you're working on a machine lending task, you might
be able to get 80 percent of accuracy within a week or
two, but to actually get 85 percent may take you
months, or it wouldn't be possible. So, yeah, I'm a big
fan on building something simple and then intrading
on that.
Kirill Eremenko: Yeah, that's very cool. Get going and then improve,
improve, improve, rather than just have the end ideal
scenario in mind and try to strive for that forever.
Nic Ryan: Yeah, that's right. And you never really learn until the
system is in production and then you probably want to
slowly get it into production as well, so test it out
another couple percent of your population, make sure
it's doing the right thing, stop monitoring for that to
happen as well and then slowly get more and more a
high percentage of it. Automate it and just kind of
going from there so yeah. See the way your portfolio
responds to the model and you just kind of [inaudible
00:53:07]
Nic Ryan: You can go for something more complicated like a
rainforest, you can maybe try some deep learning
methods. To me, I tend to try the simple one and if
that's good enough I'll stick with it. But generally
speaking, it is often the big thing as well is with
natural language processing for an application like
that there's even some very simple things that you can
do by having just even a keyword look up for some of
the fields that you know are going to be there as well,
so it's a combination of a few things as well. Attacking
it from a few angles as well. So that's bit of a trick as
well.
Kirill Eremenko: Okay.
Nic Ryan: If you know for instance from a bank statement, there
is a certain company that it always goes to, like in
Australia, Woolworths for instance. Maybe that's not
local bunk to go to Woolworths Petrol. but that's a
shame that we don't have Woolworths Petrol. That's
where the bi-gram's coming but we just have
Woolworths the shopping center. Sorry, the
supermarket. And we always know that that's going to
match the groceries and so you just have a keyword
for that, so that's a combination of simple approaches
I think is often good.
Kirill Eremenko: Okay. Very cool. Alright so natural language
processing is a really cool thing to learn. Actually I was
using ... my brother has this thing, it's called Google
Home. Have you used it before?
Nic Ryan: Yeah, I stayed at my friend's place actually in Brisbane
and he was turning the lights on and off using Google
Home. It's great.
Kirill Eremenko: Yeah, it's crazy. You can play something on your TV,
you can switch the music on ... it's just such a cool
tool and I find it's actually ... but the way, not affiliated
with Google or anything but I find Google Home is
better than Alexa from Amazon. I've used both and
somehow Google Home just catches all the things you
say, like 90 percent of the things you say. Very very
cool. So it's coming into our lives and great advice for
anybody out there to start learning natural language
processing as scary as it might be, it is going to be
more and more widespread and experts in that field
are going to be needed more and more as well. For
sure.
Nic Ryan: Yeah I think so. Yeah, I think natural language
processing is going to be good. But I think as well
there's going to be some pretty cool things happening
with, as you say, audio and computer vision as well.
So I'm starting to see some more of those projects
coming through as well where people are looking at
plans for houses and trying to work out cost of
buildings and all sorts of cool things like that.
Kirill Eremenko: Gotcha. Okay, so we're coming slowly to the end of the
podcast. I wanted to ask you ... you mentioned you
liked mentoring and helping people progress whether
its in basketball, it's in their professional lives, in data
science, and so on. What would your one biggest piece
of advice be for someone who is starting out into the
field of data science and they might have prior
experience in other areas, maybe not, but they're quite
new to the space of data science, what would you say
to them and what would your one biggest piece of
advice be for them to help them become successful?
Nic Ryan: I think, for me, I was pretty late picking up
weightlifting. I do gym 3 times a week and I've only
really started that for about 2 years. And when you're
doing it, when you first start, it's extremely painful. I
was walking like Robo-cop that day and it was agony,
and all I was doing was hurting myself and I didn't see
results and I wasn't getting any stronger and it was
just ... so you sort of keep it up and you keep it
consistent and it's 3 days a week and you lock yourself
into this routine. You keep doing it. And then, over
time you start to slowly see results and it starts to
slowly get easier and you're starting to be able to do
more and more.
Nic Ryan: And so, that's a great analogy as well for learning data
science. It really does ... initially it's painful, but if you
stick with it and if you do set up a schedule you will
have success every time and you will look back on it in
a year and think "wow I know all this stuff" but when
you're sitting in the hurt locker doing it, it doesn't
really feel like it's much fun at times. But that's all I'd
say is consistency is the key. And just making sure
that you just keep going with it, and looking for again,
whatever's out there that can help you. And what you
guys charge for what is really a quality education. You
couldn't go to a university and get the education that
you guys are charging for a couple bucks. It's just
incredible. So there's some great resources out there,
so speak to people, find out what you need to know
and get out there and do it.
Kirill Eremenko: Fantastic. Thank you. Very good metaphor. Totally
loved it with the gym and yeah, I totally agree.
Consistency is key. Alright, so before ... first of all,
thank you so much for coming on the show and
helping us see this whole world of data science
working remotely and being a consultant to other
companies and combining the technical side of things
and the data science advise and strategy side of
things. Before I let you go, I would like to make sure
our listeners can get in touch. What are the best
places to find you, connect with you, and maybe follow
your career?
Nic Ryan: Yeah, definitely. LinkedIn is probably the place to go.
I'd say yeah, just connect with me on LinkedIn.
Kirill Eremenko: Awesome. Okay, cool so we'll share Nic's LinkedIn in
the show notes. And I have one final question for you
Nic.
Nic Ryan: Yeah.
Kirill Eremenko: What is a book that you can recommend to our
listeners to help them succeed in their careers?
Nic Ryan: There's a book that I have here that is really quite
good. It's The Structural Interpretation of Computer
Programs and it teaches you how to code through
scheme, and it's more about methodology and
understanding problems and decomposing problems
and it's actually a good book, but it's a bit heavy. But
what I've discovered fairly recently is a book called
How to Design Programs that also uses scheme as a
teaching language and I think for someone starting out
... 'cause I think a lot of people go down the path of
learning a language and not necessarily how to solve
problems and this book is a bit different. And it also
has supporting software as well [inaudible 01:00:21]
that helps you out to build these programs and
schemes so I'm a real fan of that book and I reckon
that learning the methodology as opposed to a
language would be good for someone staring out. And I
wish I would've seen that book earlier. Hopefully
someone finds that interesting.
Kirill Eremenko: That's cool. So what's it called again?
Nic Ryan: How to Design Programs.
Kirill Eremenko: Oh.
Nic Ryan: I'll send you a link for it. It's got supporting software.
You can write your own little programs in scheme. It's
a functional programming.
Kirill Eremenko: Okay, gotcha.
Nic Ryan: It's cool. It actually sort of teaches you to break apart a
complex problem into little parts and be able to code
little functions and it's ... I'm just starting it now but
it's really quite cool.
Kirill Eremenko: Okay, cool. So we'll share that in the show notes. And
on that note, once again, thank you so much Nic for
coming on the show. Been a great pleasure chatting
with you and yeah, hope to catch up sometime soon.
Otherwise good luck with all your projects that are in
your pipeline.
Nic Ryan: Oh, likewise Kirill. Absolutely a pleasure and thanks
so much it's been wonderful chatting to you.
Kirill Eremenko: So there you have it, ladies and gentlemen. That was
Nic Ryan, Data Science Consultant from Bundaberg,
Australia. My personal favorite part of this podcast
was the whole combination of the two things that Nic
did. I didn't realize this before the podcast but it's
really cool to see that on one hand he does technical
projects and helps companies actually with the code
and the modeling side of things, and on the other hand
he has a space in his career where he goes into
companies and helps them with the data strategy, how
they can apply data in projects, and also mentors their
employees and staff. I think that's a really cool way to
combine those two aspects in a career and maybe that
will be helpful to some of our listeners as well.
Kirill Eremenko: And as usual, you can get all the show notes for this
episode at www.superdatascience.com/235. That's
superdatascience.com/235. All of the things that we've
mentioned on this podcast will be there, including a
URL to Nic's LinkedIn. Make sure to hit him up and
connect with him there as well. On that note, thank
you so much for being here today. I look forward to
seeing you back here next time. And until then, happy
analyzing.
