Show Notes: http://www.superdatascience.com/113 1
SDS PODCAST
EPISODE 113
WITH
MICHAEL COLELLA
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Kirill: This is episode number 113 with Senior Analytics Consultant,
Michael Colella.
Welcome to the SuperDataScience podcast. My name is Kirill
Eremenko, data science coach and lifestyle entrepreneur, and
each week we bring 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.
Hey guys and welcome back to the SuperDataScience
podcast. Today I’ve got an interesting episode lined up for
you. I literally just got off the phone with Michael Colella who
is a business analytics consultant and he travels the world.
We were actually right now, as we were talking, he was in
Stockholm Sweden and he’s getting on a plane to go back to
Chicago for Thanksgiving. It was a very interesting podcast
and what I really liked about today’s session is how driven
Michael is to grow, not just in his career but in his life as well.
And we talk a lot about that. If you look at his LinkedIn, you
will be shocked at the amount of courses and amount of
certifications that he has done and is currently doing. He is
currently a consultant and he is still at the same time doing
his master’s. He’s studied neuroscience, he’s studied
business, he’s studied finance, he’s studied analytics, he’s
doing a Master of Analytics right now and at the same time
he’s studies on Coursera, on Udemy. He does different types
of certifications for work and outside of work, a very
interesting life-long learner like a lot of us listening to this
podcast. I’m sure a lot of you guys are also life-long learners.
We talked quite a bit about that. We also discussed how he
integrated his passion for travel in his career and I found that
very interesting and very inspirational as well that he knew
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that he was passionate for travel and he managed to build a
career for himself that included that component, which is
very important that we always do what we love and what we’re
passionate about. We don’t sacrifice our passions for other
things.
Another interesting thing that came up on the podcast was a
break that Michael took during his life. For three months he
went away to another country just to reassess his life and
what he wants, and to align his future strategy in how he’s
going to build his career and other things. So, a very
interesting podcast overall, can’t wait for you to check it out
and without further ado, I bring to you Michael Colella,
Senior Business Analytics Consultant.
[Background music plays]
Kirill: Welcome everybody to the SuperDataScience podcast. Today
I’ve got Michael Colella, a business consultant from all over
the world, on the show. Michael, welcome to the show, how
are you going today?
Michael: Thank you very much, Kirill. I’m doing pretty well. I’m out
here in freezing cold Stockholm, Sweden. It’s great to hear
from you and be on the podcast.
Kirill: That’s awesome. It was really cool. When I started this
podcast, usually I say hi with video, and I was like Michael,
are you in a hotel right now? And it’s funny because I’m also
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in a hotel in San Diego and you’re in a hotel in Stockholm.
It’s just a funny situation, I think.
Michael: Absolutely. I thought that was pretty funny as well.
Kirill: Cool. Your flight got delayed, right? Is that what’s happening?
Michael: Yes. I was supposed to fly home to Chicago for the
Thanksgiving holiday in the States yesterday and there was
a massive delay, and we found out the plane was basically
non-functional, so 200 people scrambled for hotel rooms. I
was lucky enough to find one near the airport.
Kirill: Thanks a lot for waking up at 4:00am to jump on the call
today.
Michael: No problem. With pleasure.
Kirill: What were you doing in Europe, if it’s not a super-classified
secret?
Michael: I’m currently working for a supply chain and logistics
consultancy. We build optimization software and advanced
planning and scheduling software to solve complex planning
puzzles. My current project is working with an aviation client
in Stockholm, Sweden, so I came out to the Netherlands for
a while where our home office is, that way I could easily go
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back and forth between the client’s site and completing work
with the team. We had some meetings this week with the
client in Stockholm and the flight just got cancelled. I’m lucky
to still be here on Thanksgiving.
Kirill: That’s awesome. Oh yeah, it’s Thanksgiving so you’re not
going to … Well hopefully you’ll get back before it’s the end of
the day on Thanksgiving.
Michael: Yeah. Absolutely. I’m trying to surprise my family, they don’t
know I’m coming back.
Kirill: Awesome. It’s really funny how you’re working for an aviation
client and at the same time the plane got cancelled. It’s like
an ironic situation. That sounds pretty exciting.
Tell us a bit more about yourself. You seem to have a very
interesting career, or very interesting role right now where
you’re consulting companies- I’m just reading off your
LinkedIn – in countries such as Netherlands, Sweden,
Germany, Italy, Brazil, Canada, Colombia, Uruguay, China
and Spain. That’s a huge list of countries. How did you end
up in this position?
Michael: Ever since college and before, I really had a strong
international focus, so over the last seven years of my career
I’ve had the opportunity to work across different geographies
with diverse teams. Something that I’m really passionate
about even outside of data science is international travel,
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languages, and working with people of diverse cultures. I find
that very inspiring. I’ve had projects and different initiatives
in a lot of those countries and had the pleasure of working
with people from those countries and on to my project teams.
I think it’s had a huge impact on my career.
Kirill: I really respect that when you’re passionate about something,
travel and languages and cultures, and then you integrate
that into your career, you find ways to make it happen. Your
career is a huge testament to that. That if people are
passionate about something, they can get it. Where there is a
will there is a way, and it’s really cool. Walk us through this.
You studied at the University of Chicago. What did you study
there and what happened afterwards?
Michael: I’m currently a master’s student in the Master of Science in
Analytics program at the University of Chicago. What we
focus on is everything from mathematics, behind different
tests and approaches to data science and analytics to the
actual communication side, to also things like deep learning
and machine learning and time series analysis and
forecasting, and advanced Python. These are all topics I’m
quite interested in, I love working on these topics and I really
just aim to continue develop proficiencies with all those
different concept areas.
Kirill: How did you choose this degree? It sounds very good.
Michael: My background, started off in medical research doing
neuroscience research on both cognitive and behavioural
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neuroscience research during undergrad. There was a big
focus on analysis in order to present findings. From the
beginning, I had a background in applied statistics and kind
of a research or analytical mind set, and I decided that as my
career progressed and I got work in consulting on the tech
side of things with SQL and Teradata, and Microsoft SQL
Server, and some different BI tools, that this is really what I
like to do. Then I eventually explored quite a few courses on
Coursera and Udemy and then also including the
SuperDataScience set of courses. Really, after taking enough
of them I just decided I’m serious enough about this, where I
would like to get a formal master’s degree. While I don’t
necessarily see it completely necessary for success in the
area, I thought it would help build a solid foundation
especially going into job interviews, having that as a reference
point.
Kirill: Okay, gotcha. That’s a very interesting progression, from
neuroscience to now deep learning and AI and statistics and
things like that. I also see you studied at the Harvard
Business School in business analytics and finance and
economics. You’ve done everything, man. This is crazy. You
guys, you’ve got to check out Mike’s LinkedIn, he’s studied
for all his life. It is like so many different universities that
you’ve gone to. Is this something you just do for fun?
Michael: I’m constantly learning, and I’m a very curious person. The
thing that makes me laugh now as a 29-year-old is looking
back. During undergrad I wasn’t somebody who studied and
knew exactly what they wanted to do, but I did have a trust
in the sense of, I will find that out through trial and error. For
me it started off with maybe the assumption I would study
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medicine or business, coming from the family, studying the
human brain, my undergraduate major and minor were in
psychology and biological sciences. That’s where I got the
neuroscience flavour of things and then as I took more
statistics courses and then post-graduation took a lot of
learning outside of my 9:00-5:00, I think it just boosted my
career. When I saw that value was there for my career, it just
inspired me to keep going with that. I think eventually I’ll
pursue maybe a doctorate but I’m taking it one step at a time.
Kirill: Gotcha. That’s really inspiring. Looking back, because you’ve
studied so many different things. Life might change in the
future but right now it doesn’t look like you’re going to be a
neuroscientist or a psychiatrist or psychologist. Looking
back, do you regret choosing that career path at the very
start?
Michael: That’s a great question. I get that question a lot, and when I
think back, I definitely don’t regret it. Starting, studying that
psychology and neuroscience, it definitely had a formative
impact on the way I think about things. I think right now and
into the future, my interest is to build stronger competencies
in AI and then that’s really where I want to see my career go.
I think psychology has a direct relation to that. I think one of
the most complex things that we as humans try to
understand is the human brain. What I saw with different
psychology courses and actually working with patients with
various mental developmental disabilities or disorders, is just
how complex things can get. So I think there’s that
component and then also just the team leadership
component. I’m one of those people that believe there is a
value to a liberal arts education that’s not dead yet. I
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definitely have a strong mathematics background, but I think
that background in psychology has helped me understand
teams and lead teams and really try to focus on the different
ways I can motivate teams.
Kirill: Okay. That’s a very apt answer. I totally agree that deep
learning and AI have a lot to do with psychology and that will
definitely be helpful down the track, especially as these fields
evolve. Tell us a bit more. You’re still pursuing education, it
feels like it’s a lifelong thing for you, which is very cool, I think
that everybody should be like that. But at which point did
you start thinking about building a career, starting a job, how
did you get into consultancy? What was your first step in that
direction?
Michael: After my first master’s in Psychology, I took a bit of a break,
you could say, to Brazil. I started volunteering to teach
English in the favelas, which are the slums. I really wanted
to take that time to think more deeply about what is it exactly
I want to do and what is my passion. I also wanted to make
sure that I didn’t just blindly follow a linear trajectory. I
wanted to do something interesting that if anything else, I
could look back and say, hey, those three months were worth
it. For me what that time served as, is a time to think deeply.
Did I want to continue down the more medical type route or
did I want to try to leverage these skills that I picked up and
developed within the scientific community in business? When
I got back to the States, I decided to definitely go with the
more business flavour and then obviously that international
experience inspired me to get involved with companies with
those diverse teams and that offered me the opportunity to
travel internationally. I figured that consulting would be kind
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of the reflex as far as what to get into. I feel like consulting is
nice because it respects diverse backgrounds of individuals.
You might be a chemical engineer that wants to go into
business and there is generally a home for you within
consulting. Of course, there’s some core skills to develop
there but I think that’s been the natural fit for me.
Kirill: That’s really cool. There’s so many things I want to talk about
right now, like branching out of what you already mentioned.
But just quickly, so you came back and did this job offers just
fall on you or did you have to look for them yourself?
Michael: I would say they definitely didn’t fall on me. There was a
period during which actually I would say it was a bit difficult
to find the right role. That was probably due to maybe a slight
lack of clarity on my end, as exactly where I might fit in. But
eventually I found that out. I think that’s really where
perseverance came in to say okay, I’m exploring different
opportunities, interviewing for different types of roles, I’m
going to find something that fits. Then that further inspired
me to continue my education because I thought, hey that’s
not only going to make me more marketable, taking classes
from either a business or a data science standpoint, but it’s
going to further develop my skill set and give me an edge on
people outside of the 9:00-5:00. I’m a firm believer in
whatever you do between 6:00 and 10:00 will really determine
your future, and those are the first principles I tried to use
going forward. And I think it’s worked out so far.
Kirill: I’m glad you touched on that because I was about to ask, was
it hard to combine a full-time job and education at the same
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time. Did you have to make sacrifices in order to get through
that?
Michael: The major sacrifice was on sleep. My sleep took a hit but
luckily, I’m able to function pretty well on about five hours a
night. The last two weeks I think I averaged about three,
three-and-a-half, which is not ideal. It just takes
commitment. I think once I found my passion especially as it
relates to analytics and business and data science, it was
easier for me because I didn’t feel like I was necessarily
sacrificing something in a painful way, but sacrificing
something in a way of, hey, this is really what I want to learn
more about, this is really what I want to do. I didn’t want to
let anything stop me.
Kirill: That’s really cool. I think everybody has that time through
6:00 and 10:00 and a lot of time we spend it doing the wrong
things or not pushing ourselves. Like sometimes you’ve got to
rest and relax but I have friends who just watch TV or just go
to the bar every night or just do nothing and I think it can be
put to good use sometimes. It doesn’t necessarily have to be
always, you can’t always be working and studying, but
sometimes, occasionally you can and probably should.
A couple of interesting that you mentioned. The one I want to
start with is the whole taking a pause and going to Brazil and
teaching English for three months. That’s such a cool thing.
I think so many people, myself included, would benefit from
that. That would give clarity, that would give a time to
reconsider things, assess things. Tell us a bit more about
that. If you’re talking to someone who’s never, ever, taken a
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pause in their life and they’ve always gone like school, uni,
maybe they did a gap year but that was more for fun and
travel, and then they get one job, another job and so on. How
would you help a person like that plan something like what
you did for themselves? What are the things to take into
consideration?
Michael: That’s a great question. I think it’s really important to take
that pause and also to just expand your comfort zone. That
was a huge reason why I decide to go there. Looking forward,
I feel like one thing that inspires me, I feel as someone gets
older, by default you have less time. Whether that means
literally or based on different commitments. For me I wanted
to at least if nothing else, take this time to experience
something that’s maybe non-traditional. There are definitely
organisations people can reach out to, to sign up for different
types of volunteer activities. To be honest, at first, I was just
going to go to Italy and teach English at a camp there. But I
had been to Italy a number of times already, my dad has an
Italian background, but my thought was, let me do something
completely different and something that makes me feel alive.
I didn’t speak Portuguese at the time, I had never taken a
Portuguese class and I didn’t know anybody in Brazil, but I
found an organisation through New Zealand that paired me
with an in-country volunteer organization, kind of as an
intermediary. I would say that’s something that people
should think about. As, hey, do I want to do something
different before I plug back into the matrix, or do I want to
maybe take some time to think about what it is I really want
to do? At the time different family members and friends
thought this guy is crazy, why is he doing this? But I would
say that would probably be the single thing that had the
biggest impact on my career as well as my mindset related to
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my career and then just my personal development. It’s hard,
at the time, to see maybe just how big the impact will be or
convey that or articulate that to people, because it’s
impossible to predict the future with 100% accuracy. But I
would say that just believing in yourself and saying, hey, I
know something good’s going to come of this because I’m
going to literally will it to happen. And then it did. It’s come
up during job interviews and it’s always gotten that extra
pause and that additional discussion as well as interpersonal
interactions with other people, with friends and new
colleagues.
Kirill: Gotcha. You didn’t know Portuguese at all when you went
there. How did you teach English, how does this work?
Michael: There is an in-country organization that connected us to
another non-governmental organization in the favelas.
Basically, what happened, it definitely adds a layer of
complexity. At first, we started teaching a lot of teenagers as
well as little kids. They have a lot of energy and they’re not
speaking English, so it kind of forces you, it puts that extra
pressure on you to at least learn the basics, so you can
communicate. But there was also a willingness to learn, so
we were able to convey especially with at first the help of a
translator and then Google Translate, what different words
were in Portuguese vs what they were in English. The kids
seemed to be interested because they see all these English-
speaking movies and TV shows and listen to music in English
language, so they are kind of by default motivated to learn
more. Then it was really just delivering on that and then I
really believe sometimes the best way to learn things is to just
jump right in the pool and try to swim. I was surrounded by
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Portuguese all day, every day. There were some people that
spoke English, but I would say it was less common at the
time, it was just before the World Cup. It really forced me to
learn more and quickly, when I got there I was even dreaming
in Portuguese. I felt constantly stimulated and for me, just
because I’m pretty hyperactive, that kept me interested. I
knew Italian and Spanish so for me it was just a matter of
listening a little bit more closely and then seeing the words in
Portuguese and then just changing the sounds. No doubt a
lot of the words are very different from Spanish or Italian, but
I initially picked it up by ear and then when I got back to the
States I took some formal classes.
Kirill: Gotcha. But for someone who doesn’t know any other
languages apart from English, do you think in three months
they can pick up Portuguese to a good enough level?
Michael: Yeah. I definitely think so. Coming from a full immersion
perspective, that’s the best way and the quickest way to learn.
I think a lot of people start with taking classes, maybe they
go once or twice a week and have some homework in their
home country, which I think is good to lay a foundation but
complement to that, you could actually go visit the countries
or try to live there on a short term or vacation there on a short
term and immerse yourself in the language. Or do what I did
and just go kind of blindly and then try to scale up from zero
very quickly. I definitely think it’s possible and it’s worth a
shot.
Kirill: That’s so cool. That’s really inspirational thing. I’m just going
to ask one more question in this because it’s so new to me
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and a very interesting area. When you go overseas like that,
do you still check your phone, check your emails and so on,
or you just cut everything out completely in order to focus on
whatever you’re contemplating for those three months?
Michael: I would definitely say there were periods of being completely
disconnected that were very liberating. In Brazil at that time,
it wasn’t as easy as it is now to have a certain cellular
provider. I’ll keep them unnamed, but they provide
connectivity in 144 countries etc., it was more of a thing
where, hey I need to get an in-country phone and kind of a
pay-as-you-go. That was a wonderful experience at times to
be completely disconnected and fully present with the people
I was with. I felt like it forced me to learn a lot more about
them and focus on that truly human experience instead of
constantly being distracted by notifications. Actually, that
was one of the hardest things to adjust to coming back to the
States, was now people expect me to be connected all the
time. You get used to it again, but it was just a brilliant
experience.
Kirill: Fantastic. Thanks a lot for that excursion into the world of
going and exploring yourself, and understanding what you
want. Let’s get back to your career. Once you came back, you
were in consulting, tell us a bit more about what exactly it is
that you do. Of course, without disclosing any sensitive
information or practices, but just out of curiosity, what does
a consultant in analytics do that you travel the world, and
what kind of projects do you work on?
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Michael: In my current role, it involves working on different projects
within supply chain and logistics globally. For me, in my
career, I’ve always marketed and felt comfortable being
somewhere in between what I would view as the traditional
software developer and someone completely on the business
side. I think that spot right in the middle is really what
analytics is today because there is obviously the technical
proficiencies and the comfort with coding and reading code
and interpreting different types of analysis, but also the
business or strategy or communication side. Being right in
the middle is where I have functioned on different teams over
the last three to five years, and that’s kept me super
interested and varied up my day and my schedule a bit so
that’s been great. Currently, the organisation I’m working for
will be working with companies not only from the aviation
standpoint to maybe optimize their workforce planning,
aligning with flight information systems which as I saw first-
hand, flights can get cancelled, and then also working with
ports and container terminals, manufacturing processes.
Analytics and computer science is definitely applicable in
these areas because all of these companies globally are just
trying to … they use the word digitalization. I’m not quite sure
if some of these terms are words officially but they’ve become
buzz words or industry terms where, hey, they have these
setup processes and not only are they trying to optimize
them, but they’re trying to get planning out of excel or more
manual planning. That’s really the value that we add
currently, we help solve these advance planning and
scheduling and supply chain puzzles from a technology
perspective. Prior to that, a different company I worked at,
the teams were quite diverse, and we had overseas teams, but
the client I was at was in downtown Chicago, it was a major
healthcare company and even within that, there’s a lot of
different tools we used from SQL to Teradata to concepts like
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working with data lake or DUP. But also, it’s quite interesting
to be able to formulate the proper message to the business
stakeholders and internal team that might be a bit more
technical. I was really used to bridge that gap and it’s been
the right fit.
Kirill: Okay. That’s a really interesting description. I’m very curious.
Can you give us an example of a supply chain puzzle as you
said, just hypothetical? It doesn’t have to be a real project
that you’re working on or have worked on, but a hypothetical
example of a supply chain puzzle that a consulting firm like
yours would address.
Michael: Absolutely. I’ll resist the impulse to generally talk about the
current engagement that I’m on. While I do think it’s quite
interesting, but to take care there. For example, let’s say a
major canal in the world or a container terminal. You’ve got
these asset ships coming all over the world, whether they are
from Singapore or Shanghai, or the port of Rotterdam, or
somewhere in Australia or South America, to different
locations. They have their own on-board computer systems
and they also have a variety in scheduling, but they have a
variety in their cargo. They might be carrying hazardous
materials, they might be carrying perishable materials, they
might be carrying more traditional consumer product goods.
All of these containers are all stacked on top of each other, so
it gets pretty complex because you’re basically dealing with a
3D puzzle where you need to be able to identify when this
vessel comes into port, to berth, which is one of the terms
that we use, it’s just when the ship is aligning with the dock
and getting ready to be unloaded. You need to know where
these different containers are and where these containers are
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going. So, one big ship that maybe comes into the port of
Rotterdam, might have a few hundred or a few thousand
containers and these containers all have to be accounted for.
They have, like I said, different types of goods so they’re
located in different areas of the ship but also, they all have
their own end-destination or maybe groups of them have their
own end-destination. The puzzle lies in being able to unload
the ship in the correct order, or the most efficient or optimal
order in order to make sure that these containers get to their
final destination but even just their intermediary destination.
Trucks are coming into ports to pick these containers up,
there are forklifts, there are automated cranes that will go
and try to unload the ship based on data that was received
on where a said container is located. Then on top of that,
there are all these complex labour rules and regulations, so
these ports might run 24 hours a day, 365 days a year to
make sure everybody gets the food and the products they
need. You have to factor in all these unique constraints as we
call them, within countries in different areas of the world from
the labour rules and regulations to union rules and
regulations, which include like different rest periods that are
required and different breaks as well as the length of their
shift. These software optimization solutions, they have to
account for all these different variables from the actual labour
rules and regulations, to the planning at the ports or
container terminals to unload these vessels, which involve a
number of different components to actually consider the
information of the vessels. What’s on the ship and where it’s
going and what is the timing for that ship? How quickly does
it need to be unloaded etc. There are just so many more layers
to the puzzle than even I initially thought, coming into the
role but it’s been great to learn a lot more about supply chain
and logistics and how analytics and computer science have a
role.
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Kirill: That’s crazy. I can’t even imagine how massive the software
would be and how long it would take to create it in order for
it to correctly account for all these different details that
comprise this whole operation. From your experience, how
long does it take to create a piece of software for solving a
puzzle like that?
Michael: Definitely it takes a while. These puzzles they have these sub-
puzzles. They might specifically bring us on to optimize the
workforce or they might specifically bring us on to optimize
the stock yard planning for what’s going on for unloading and
loading the vessels. The length of a project or how long it
takes to build a solution really varies. Are we building the
whole thing, which would probably take a couple of years at
least, or are we building for a scope of work that’s just a sub
component which I would say at that point will take anywhere
from half a year to maybe slightly over a year. It really
depends how complex the puzzle is but those are probably
the general ranges that I feel comfortable with.
Kirill: Very interesting. All right, that’s a very interesting line of work
and it’s very different to what we’re normally used to in data
science like R and Python programming and things like that.
Can you tell us a bit about the tools that you use in order to
accomplish these objectives?
Michael: Yeah, absolutely. The current organisation that I work for, we
partner with a specific software provider called Quintic,
they’re owned by Dassault Systèmes, I can’t speak French
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but Dassault Systèmes or DS, they have a lot of common
engineering tools or programs that are used, specifically the
Quintiq software, it solves advanced planning and scheduling
puzzles across all sides of supply chain planning and
logistics. Then we have some in-house tools that we have
developed for rail cargo optimization. Those are the actual
software platforms and then within that we interface or we
can connect to any system. There are definitely SQL
components involved, so you could be talking about Microsoft
SQL Server and then a lot of the clients that we work with,
there are specific BI tools they use. Of course, the super
common one is always trying to get their planning out of
excel, but really we just take pride for being able to interface
with any systems that they might have as well as file formats
whether they’re XML or HTML or JSON. It’s really a variety of
systems and integrations that we work with, but at the same
time the actual software that we develop comes from Quintiq,
so they have the world record on solving a lot of different
puzzles. It’s really a puzzling software that’s quite nice and
then, like I said, we have some in-house solutions for some
sub sets of tasks within supply chain and logistics, mostly in
the rail cargo space. But there are some other popular
softwares like AIMS, I know BCG they use AIMS and some
other tools.
Kirill: Okay. When you say you develop software for them, what I
gathered is that you don’t sit down and code something in C-
sharp (C#) from scratch or in Java. You actually already have
these programs, platforms, in which you kind of just … It’s a
more high-level tool where you don’t need to encode all the
mechanics of the tool itself, you just need to encode the
problem of the client. Is that correct?
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Michael: I think that’s a very true statement. The language that’s used
for this software platform is called Quill. I’ve heard it
described in different ways, but I’ve almost commonly heard
it’s some sort of mix between Java and C#. It is object-
oriented, but we’ll basically encode, like you said, the actual
puzzle or the solution to the puzzle or some combination of
the two, and there is the whole software development lifecycle
of gathering requirements to writing technical documents
that can be followed for the development processes and then
also writing the functional or more business type of
documentation and it’s really beautiful when the whole
solution comes together. Definitely it takes a lot of hard work
and a lot of listening but that’s pretty much what we do to
build a solution.
Kirill: Okay. How long did it take you to get the grasp around how
to do that?
Michael: I would say the whole training process it takes at least for the
first level of certification, maybe about three months. Looping
that in with other work that you’re doing. Like many things,
I think there’s a natural progression of learning how to use
different tools and interact with them and derive value from
the data with them. There are formal certification processes
to go through with our software partner to feed to our
proficiencies and then that’s something that the clients look
at, certifications, they serve to provide trust with the clients
you’re interacting with. The first level, three months and then
it gets progressively harder, there’s more work involved to get
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the higher levels of certification but that happens through
time and actual project experience as well.
Kirill: Okay, gotcha. Out of the soft skills that you use on the jobs
which are obviously very important because you need to get
that information before you can go and do the technical side
of things, what would you say is the most important soft skill?
Michael: I would definitely say listening. There is our standard
industry solutions to a lot of these planning puzzles in my
current role that require customization, and that
customization piece is key, so that’s where that listening skill
comes in. Then being able to communicate that, not only
back to the client so that they’re confident that you
understood them, but communicate that to your team, which
is a diverse team; people who studied econometrics to
traditional developers, to people on the business side. It’s
always interesting communicating with people on your team
with different mind sets, experience and background but also
like I said, being able to listen to the client is super important,
that requirements-gathering. That way the analytics that are
conducted can be done in the right way and really serve a
business purpose beyond just being an interesting problem
to solve.
Kirill: That’s a very interesting description and I totally agree that
you need both. You need to be technical and you need to be
able to speak to people in order to get that information that
you need or convey the information back to those who you’re
dealing with. What I wanted to talk about next is, you
mentioned certifications. You need a certification that takes
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three months to get that, then the next one is harder and
harder. What I see on your LinkedIn is that you’ve done a lot
of extra certifications, you’ve done close to 10 or maybe even
a dozen courses on just Coursera alone. Obviously, that’s in
addition to your studies, in addition to your work. What keeps
you going, what keeps you motivated to do more courses on
Coursera?
Michael: I would say, just looking at even just data science and
analytics job descriptions as well as consulting positions
related to that, these days there’s just such a “word vomit” of
requirements, just everything. I’ve seen in practice that it is
true that they’re going to list their Christmas list, but you
don’t necessarily need to know how to do every single one of
those but understanding the data structures has been key. I
think that translates to all these different certifications. The
approach I’ve taken is, hey, I understand the data structures
related to this already or I need to take these courses to have
an increased level of comfort with data structures in a certain
way so these courses, again, really came out of looking at
different job descriptions but then also I think that
foundation in data structures is important because then you
can go in and learn these different tools a lot more easily
because you’re understanding, okay this is what’s maybe
standard or I’m used to and I just need to tweak that thinking
a little bit to use this tool, and this is how this tool will
respond or this language or this platform will respond to this
slight tweak. I think that’s really what it’s been for me. And
then also I’m just super curious. I feel like the more I learn,
the more I realize I don’t know, and that’s been a very
humbling experience for me, so I think it’s this idea of kind
of the “open sourcing of education and knowledge”, it’s just
changing the world. Because now people that normally
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wouldn’t have access to these classes, normally you go to
university, you have to pay $5,000 for these classes, you can
go take them for relatively nothing or a much cheaper price
point online and then still build the same skills. I think it’s
just incredible.
Kirill: That’s very true but at the same time do you ever feel
oversaturated? Do you ever feel that you’re learning things,
new things, but you’re forgetting things that you learned
before? Not like immediately before, but you took five courses,
now you’re taking a sixth one and you’re forgetting what you
learned in the first one. How do you go about that, because I
feel that with this availability of education, a lot of people are
afraid to go and learn more and more stuff because they kind
of know that if you’re not using some knowledge, and in your
case, you’re even going out of your way to learn things that
are probably not directly related to your role right now? How
do you go about retaining that information, and is that
something that scares you off from learning more?
Michael: It’s definitely a significant part of the learning process and I
think over time certain things get filtered out. But having at
least that comfort that you can say, hey, I’ve worked at the
tool, I understand the tool, that if I needed to come back to it
that ramp up the process or that relearning process to get the
cobwebs off is a lot quicker. But to your point, I think it really
comes down to what you’re using on a daily basis is really
what you’re going to likely be the best at. I think on that same
note, that’s really about going deep on things. In collecting
different proficiencies and certifications, I’ve tried to keep in
mind that while that might serve its purpose, it’s also
important to spend enough time with one tool to really go
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deep on it. That’s something that has motivated me especially
with Python and R, two things that I think regardless of the
role and the specific software tools you are using, you can
apply those to any role and any setting. One of my big
mentors, he’s a lead launch engineer at Google, he’s got about
10 years on me and he’s a traditional computer scientist and
that’s something that he shared with me and obviously it
worked for him, at least from a role perspective. I’ve tried to
really keep that in mind, to go deep on topics, not just take
one or two courses but like with Python I think I’ve taken six
or seven. Then trying to use that on passion projects outside
of class or work. That’s really how I think you get good at it,
whether it’s a Kaggle competition or a project with friends or
other students or colleagues on some interesting problem.
Kirill: Awesome. That’s a great answer, going deep will help you
understand the tool much better and retain that knowledge
for longer. All right, I’ve got a list of rapid fire questions for
you, are you ready for this?
Michael: Yeah, absolutely.
Kirill: What has been the biggest challenge for you ever in this
analytics role? Or in this analytics career?
Michael: I would say, piggy-backing off our last conversation, just the
amount that you have to learn. I think it’s been twofold for
me. It’s inspired me to spend more time with topics and also,
it’s definitely a factor that I think maybe scares a lot of people,
but I think there’s a natural progression to that learning and
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it’s also a constant challenge in the right way, it’s like, hey I
don’t know how this works but I’m going to figure it out. And
I think for me that tooling around is just very inspiring for
me, I think data science and analytics is definitely a place for
people who are naturally curious, and they want to keep
learning and they like challenges, they’re not comfortable just
sitting still.
Kirill: Great answer. I love it. The next one is, what is a recent win
that you can share with us, that you’ve had in your role?
Something that you’re proud of.
Michael: I would say just building trust with the client. There’s a lot of
companies out there these days with different software
platforms that develop in different languages and I think
translating analytics into practice and building trust with the
client. Saying hey, based on the questions you asked and the
requirements you gather and how you communicate, that’s
really the difference sometimes. Given everything else equal,
I think people are, by pure market pressure, being called
upon to learn a specific set of skills or tools or software
development languages, but that trust has been the
difference. I’m really proud of that with the current
engagement, I think that they have a strong trust in us so
that’s huge.
Kirill: That’s awesome. What would your best tip be for building
trust?
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Michael: I would say listening is key and then asking the right
questions. Because when you’ve taken your time before a
meeting or an engagement to really prepare and understand
the puzzle or the complexities or intricacies of the potential
work or the work of that specific client, that will come out in
your questions. I think that’s one thing that other people
notice- how deeply did you think about the problem at hand?
Because these are experts you’re dealing with that often know
a lot more detail related to a topic than we do as the
consultants, at least initially. But then we come in and we
become the experts at showing them how to translate their
puzzle or problem into a solution. That initial set of
questioning and listening, I think that’s how you build the
trust and then it’s wonderful when you sit there, and it clicks
with them and they say at the end of the meeting, I really feel
that you guys can do this.
Kirill: Okay, that’s a good tip. What would you suggest if somebody
is in an engagement as a consultant or even in their own
company, and they’re dealing with a person or talking with a
person who just has his bias and resists this whole idea that
analytics needs to be involved, that somebody has to be
helping them sort this problem out? They think they know
better and stuff like that. In such problem cases, what would
your approach be? Because this is still your client or in the
workplace, this is still the person that you’re trying to help,
that you need to help in this project. What would your advice
be there?
Michael: That’s a great question because I feel like that comes up so
often. Regardless of the company I’ve been at over the last five
to seven years, there’s always some sort of resistance to
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change and that’s probably the most difficult thing to break
through at clients especially when you’re coming in as a
consultant. I think sometimes they might have an industry
where consultants are coming in. Practically, I would say I’m
showing the value, so almost giving a demo of sorts, whether
it’s some certain analysis in R or Python or some other
language, or if you have a demo for a related planning puzzle,
that speaks volumes. Because what you can do with the
client in that regard is give a certain planning scenario that
they might have during their day or their 9:00-5:00 and kind
of have them work toward a certain success metric manually
or as they currently do, which might be manually or semi-
manually. But then shown them the power of the solution or
the analytics or the tool and how it can add value and make
their life easier. Once you show them that you can make their
life easier, I think that value really just transcends any sort
of biases or walls they might have up. That’s how I’ve seen
success getting in with the clients, so to speak.
Kirill: That’s a great way of putting it because, who doesn’t want
their work to be easier? Everybody wants that, so I think
you’re on to something there. Show them what’s in it for
them. Okay, what is your one most favourite thing about
being in the space of analytics?
Michael: I would say the constant challenge and that goes hand in
hand with all the different methods and tools that are out
there. I think the pace of evolution of the field of analytics and
data science is just so fast already and it’s just speeding up.
Whether we’re talking about machine learning or deep
learning or AI, there’s just so much out there that it’s
humbling but it’s also so exciting. It feels like you’re on the
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front of the curve of the normal distribution of the world,
you’re part of that group or cohort of individuals that’s an
early adopter. For me, I’m a big believer in “moon shots” so
being on the forefront of something brand new is really what’s
most exciting.
Kirill: Amazing. Yeah, I totally agree. It’s just crazy how things are
developing so quickly especially in the world of AI. You never
know what’s going to happen in, not even five years, the next
year, you don’t know what’s going to come out and it’s always
a surprise when it does. Now I’ve got a philosophical one to
kind of like wrap things up. I love asking this question
because people in different positions have different
perspectives based on their experience. From what you’ve
seen in the space of analytics and data science and AI, deep
learning, where do you think this whole space is going and
what should our listeners prepare for to be ready for what’s
coming in the future?
Michael: A couple of things. I think not only are a lot of initiatives being
set up to have a better impact on the environment, make our
lives easier as we talked about, but I think it’s going to get in
many ways a lot easier to get involved. I think a lot of
companies and different organisations in the tech space are
working to make things easier. Like for example with certain
machine learning tools or methods where I’ve seen even now,
which is quite interesting, some drag and drop type of
functionality. I don’t see that importance on understand the
science or the coding behind it going away, especially from a
statistical analysis perspective, but I think it’s going to get a
little bit easier for more people to get involved and then I think
once they do get involved, maybe that initial anxiety about
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learning a software language or learning how to code or
learning the math behind a process, will subside a bit.
Because they can say, hey I know kind of what the end result
is, and I know how to do this now, I’m just going a level
deeper, and that can come over time.
Kirill: I like that idea, and especially for some people it might not be
necessary to go that deep, right? It could help some people
who want to and who will eventually, but it will also enable
people who don’t really need that level of depth and that huge
level of functionality, but they might benefit from a little bit
of extra machine learning in their life. Like maybe, some mum
& dad bakery down the road who have no intention of
learning R and Python ever in their lives. But if they have that
drag and drop tool, even if they get some basic segmentation
out of it, some K-means clustering or KMN classification, and
if that enables them to run those algorithms just to better
service their customers and optimize their products and
whatever else they’re doing, that can be a great step forward.
I’m pretty excited that you mention this, it does sound like an
exciting future, not just for people in data science and
analytics, but for everybody in the world in general.
Michael: Yeah, absolutely.
Kirill: All right. Thanks so much for coming on the show, that
rounds it up for us. Where can our listeners contact you or
follow you to see what are the next things you’ll learn, which
countries you’re going to visit, and how your career is going
to progress from here?
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Michael: I would say the best way is just to contact me via LinkedIn.
My last name’s a little bit hard to spell, COLELLA, but you
can find me there and I’m sure my last name will be in the
show notes as well. LinkedIn is the best and also on Twitter,
I’m trying to build more of a social media presence, but I can
be found on Twitter as well.
Kirill: Awesome. Great, that will definitely be in the show notes. So
you guys, hit up Michael on LinkedIn and follow him on
Twitter. And one last question for you today. What is a book
you can recommend to our listeners to help them become
better at what they do?
Michael: I would say, again, the technical proficiencies are important
but there is a book that’s been extremely helpful for me, it’s
called 60 Seconds And You’re Hired! by Robin Ryan, and it
really focuses on the communication aspect of business or
interacting with clients, or just getting a job in data science
and analytics. I think that’s a way to show beyond all of the
different technical tools that you might have or languages you
might know or methods you might know. Showing your
future employer, or the people you’re interacting with can be
comfortable that you can actually talk about what you’re
doing. I’m just thinking by default when you’re giving a
presentation or a data visualization, having that ability to
communicate in literally 60 seconds or less, the value, I think
that speaks volumes.
Kirill: I think that’s a great suggestion. I haven’t read that book
myself, but I think that would even be beneficial for people
who are in the space of entrepreneurship or figuring out ways
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to use data science to help other companies as consultants
or if they need investors because 60 seconds can be an
interview thing, but it also could be an elevator pitch and
maybe that could be useful there. Thanks for the suggestion,
the book’s called 60 Seconds And You’re Hired! by Robin
Ryan. All right, Michael, thank you again so much for coming
on the show and spending some time with us here today, we
really appreciate all the insights and the amazing story. I
hope you have a lot more consulting fun engagements in the
coming future.
Michael: Thank you so much, Kirill. That was a real pleasure.
Kirill: There you have it. That was Michael Colella and I hope you
picked up some very powerful insights from this
conversation. Personally, I got two main takeaways. I usually
mention just one but this time I think it’s important to
mention both of the takeaways because I feel they’re
important. Lots of things but the two main ones. Big
takeaway number one: Michael was passionate about travel
and he knew that he was passionate about travel and he
managed to incorporate that into his career. Not just
managed, he set out to find a career that incorporated travel
in itself as a major component of the work. I find that very
admirable, that he didn’t let go of his passion, he didn’t
sacrifice, he didn’t trade it in for a big pay check or just
interesting work like sometimes you might think, if I want to
do this work, I can’t do what I’m passionate about. But that’s
not true as you can see from Michael’s example, he managed
to incorporate that, his passion into his work. He built
himself a career where he travels and does analytics, and he
does data science. That’s big takeaway number one. By the
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way, from the previous podcast, where we were talking with
Eric, he managed to do the same thing. He is passionate
about education and he incorporated education into his
career. There you go, those are two examples and it just
stands to show that whatever you’re passionate about,
whether it’s helping other people, saving the planet, helping
animals, nature, physics research, whatever it is, there is a
way to incorporate it into your career as a data scientist.
That’s number one.
And takeaway number two is that I really liked how he
described how he took a pause to go to Brazil and teach
English to children there for three months and how that was
intentional to help him realign in his own life, understand
what he wants from his career and what he wants from his
future, what he wants for himself. Because a lot of times in
life we get caught up in the moment, get caught up in all these
minutiae of life, and all these things happening around us,
like Michael said, he put it very aptly, as soon as he got back,
people expected him to be online. We have expectations that
we have to conform. These expectations are of other people
and we sometimes don’t even know what we want ourselves,
and I think it’s very important to know what we want and if
what it takes is to go to Brazil for three months and
disconnect and just find yourself there, then that needs to be
done. I really respect Michael for having the courage to do
that and for actually going through with it. I think that a lot
of people in this world could really benefit from that and have
much happier, more fulfilled lives if they truly knew what they
want for their own lives. I personally think I’m going to take
that advice on board and hopefully one day I’ll be able to …
It’s all up to all of us, I’m already making excuses, but one
day I’m going to do something similar and disconnect. Maybe
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it’s something that needs to be done regularly, maybe every
couple of years you need to go away and just find yourself.
That was a very cool excurse into a part of his life.
There we go, that was Michael Colella. You can get the show
notes for this episode at www.superdatascience.com/113,
there you’ll find the transcript for the episode and all of the
materials that we mentioned and plus you will get the URL
for Michael’s LinkedIn and his Twitter. Make sure to hit him
up and connect on LinkedIn and follow him on Twitter. Help
a fellow data scientist build out his social presence, as he said
he is building out his social presence on Twitter, let’s help
him out. On that note, hope you enjoyed today’s podcast can’t
wait to see you back here next time. We’re slowly getting close
to the end of the year, only a couple of weeks left to go, and I
look forward to seeing you back here and until next time,
happy analysing.