sds podcast episode 113 with michael …...hey guys and welcome back to the superdatascience...

Show Notes: http://www.superdatascience.com/113 1

SDS PODCAST

EPISODE 113

WITH

MICHAEL COLELLA


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


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


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


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,


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


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


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


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


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


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


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


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


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


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?


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


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


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.


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


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?


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


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


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


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


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


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?


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


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


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


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?


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


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


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


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.

http://www.superdatascience.com/113

sds podcast episode 113 with michael …...hey guys and welcome back to the superdatascience...

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