SDS PODCAST

EPISODE 95

WITH

JOSH KENNEDY

Kirill: This is episode number 95 with Regional Operations

Manager at Uber, Josh Kennedy.

(background music plays)

Welcome to the SuperDataScience podcast. My name is Kirill

Eremenko, data science coach and lifestyle entrepreneur.

And each week we bring you inspiring people and ideas to

help you build your successful career in data science.

Thanks for being here today and now let’s make the complex

simple.

(background music plays)

Welcome everybody back to the SuperDataScience podcast.

Today we've got something exciting. A couple of months ago,

we had a giveaway at SuperDataScience. It was called the

SuperDataScience skills booster giveaway. And if you were

with us at the time, you may remember we sent out an

invitation and you needed to go to this page on our website,

and then just perform certain actions, like liking a post, or

leaving a comment here and there, and you would get

entries into this giveaway to win a prize. And the prize was

your choice of 3 conferences about data science that you

could go to. And the conferences were the Strata Data

Science conference in New York in September, the Tableau

conference in Las Vegas in October, and the Open Data

Science Conference West in San Francisco in November.

And today, we have the person who won this giveaway. So

Josh Kennedy is our winner, and he lives in California, and

he works for Uber. So we chatted with Josh about his

aspirations, about how his goal is to become a data scientist

in the next year or two, and what he's doing in the direction

of that goal, what he's learning, how he's going about it. And

also, towards the end of the podcast, we talked about some

other interesting things like entrepreneurship, ideas,

execution, getting things done, and stuff like that. So quite

an interesting chat. Can't wait for you to check it out. And

without further ado, I bring to you Regional Operations

Manager at Uber, Josh Kennedy.

(background music plays)

Welcome everybody to the SuperDataScience podcast. Today

I've got an exciting guest, Josh Kennedy from Uber on the

show. Josh, how are you going?

Josh: Hey Kirill, it's great. Thanks for having me on.

Kirill: And first off, congratulations. You won the

SuperDataScience giveaway. We were giving away a free

ticket to a conference of your choice. Tell us a bit more

about that. Were you excited when you found out you won?

Josh: Yeah, I was incredibly excited. I don't know if I've ever won

any sort of giveaway before, not that I can remember. I'm a

huge Tableau user, I'm actually from Vegas, so I'll have

somewhere to stay while I'm there. So I'm really excited

about that.

Kirill: You're going to the Tableau conference, you chose that one?

Josh: Yeah, yeah, the Tableau conference in Vegas.

Kirill: That's awesome. And how did you find out about the

giveaway?

Josh: I think I'm on your mailing list. Because I've taken several of

your Udemy courses, and it came through an email.

Kirill: And then you were like, aw, I might as well, try my luck, just

click a few buttons, yeah? How many entries did you do?

You told me.

Josh: Yeah, I think I did two. One of them was subscribe to email,

which I think I was already subscribed to, and the other one

was visit your Facebook.

Kirill: Yeah. So why didn't you do more actions? You would have

gotten more chances to win.

Josh: Well, usually they're focused around like Twitter, or

Instagram, or some sort of sharing, and I never have those

logged in.

Kirill: So it was just what was easier at the time. And then you

won! That's so cool, man. Congrats. Very excited for you.

Josh: Thank you, thank you.

Kirill: With the conference, when's it going? Is it in October?

Josh: It's October 7th, yeah. I already booked my flight.

Kirill: Ok, cool. So maybe even when this podcast goes live, you

might be already at the conference! Very interesting. I'm sure

it's going to go well. I heard they have very interesting shows

going on there, it's a huge community, and lots of fun. So it

will be fun. It'll be good.

Josh: Yeah, it seems like the Tableau community in general is

pretty fun too, so I'm excited to be around that.

Kirill: Yeah, you like Tableau, right? You told me.

Josh: Yeah, a huge Tableau user. It's just a fun software to use.

Kirill: Yeah, totally agree, totally agree. And we'll talk more about

that. But tell us what you do, Josh. You work at Uber, right?

Josh: Yeah, I'm currently in the Operations Org for Uber. I sit in

San Francisco right now, but I work in a team that's based

in LA.

Kirill: Ok, gotcha. And you're a Regional Operations Manager.

Josh: Yeah, so that means I work in the Operations Org, but I do a

lot of heavy data analysis tasks, business process

development, dashboarding, basically anything and

everything that we can use data for to influence our

operations org.

Kirill: Yeah, that’s really cool. Tell us a bit about your background.

You originally are not from California. You’re from Las

Vegas, is that right?

Josh: Yeah, I grew up in Las Vegas. Actually I had a pretty

interesting development of where I came from. I’ll go through

the whole thing. Growing up in Vegas, when I was young,

abaout 16 or 17, I was a professional magician.

Kirill: Oh, wow! (Laughs) That’s so cool! I’ve never had a

professional magician on the podcast. That’s so cool. Keep

going.

Josh: I was doing that for a couple of years and I was also really

into music. I had gone to a music high school, so right out of

high school I went to Music College. Not really the traditional

path for somebody who gets into data analysis…

Kirill: And for magicians especially. They usually go to Hogwarts.

(Laughs) That’s so cool. Okay, music high school. What

instrument?

Josh: I play saxophone and guitar. I went to college for sax for a

little bit, but I quickly learned a lot about financing my free

time just basically calculating what my student loan

payments would have been if I had gone through my entire

degree. And I had always been interested in finance, so I

switched my major very quickly to a finance degree at a non-

music college. And that’s kind of where I started at. All

throughout college I worked for Apple. I was in a B2B sales

job where I was selling iPads and iPhones to the casinos in

Vegas. And then one of the casinos recruited me out of

college and right out of college I went into an FP&A position,

so financial planning, where I was at Caesar’s

Entertainment. They own Caesar’s Palace, Valleys,

Flamingo, etc.

Kirill: Yeah, it’s one of the biggest companies there.

Josh: Yeah, it is the biggest. It’s international as well. They have

almost 40 properties.

Kirill: How did they get on to you? Was it through some university

open day or something like that?

Josh: Yeah, exactly. I went to University of Nevada, Las Vegas, so

that’s one of the schools that they recruit out of. So I just

went to a networking event with the folks from Caesar’s and

I happened to just have been chatting with—I didn’t know it

at the time, he was the senior vice president of finance. If I

had known that, I would have probably been a little bit more

shy. I got along really well with him and set up an interview

before I had even left the networking event.

Kirill: Nice, very nice. Okay, so you were studying and working at

Caesar’s and then what happened?

Josh: Yeah, studying and working at Caesar’s while I was there. I

was actually really happy, I liked my job a lot, but Uber

reached out to me on LinkedIn, and Uber is one of these

companies that’s like a unicorn, you know what they say.

Kirill: You don’t say no.

Josh: Yeah, you don’t pass up an opportunity like that. And I

truthfully thought I’m not qualified for this, but what the

heck, if they want to interview me, I’ll let them interview me.

And then it turns out I got it.

Kirill: Was the interview process long? Because I hear it’s like

seven interviews with Uber.

Josh: Yeah, it was incredibly long. It was about two months.

Kirill: Two months? Wow!

Josh: Yeah. I was first interviewing for an operations position in

Vegas and the management team for Vegas was based in

Phoenix at the time, so they flew me out to Phoenix. I

interviewed with the whole team and then they were like,

“Oh, actually, how would you like to work in L.A.?” and I

was like, “I’m okay with L.A.,” and then I interviewed with

the entire team in L.A. as well.

Kirill: Wow, that’s crazy.

Josh: And eventually I moved to L.A. for them.

Kirill: And they also give you a test at the start, right? You have a

timed test where you have to solve some problems. Is that

still the case?

Josh: Yeah, it’s a pretty famous analytics test that people like to

talk about.

Kirill: Okay. Is there anything you can share from that that’s not

going to jeopardize the test for other people who are going to

take it?

Josh: For sure. If you’re well-versed in Excel, you’ll do pretty well.

It’s all Excel-based. They give you a sample dataset that

needs to be cleaned up and then they give you 20 or 30

questions that you need to answer with that dataset. And

they also have a lot of like, “Build a visualization off of this

data and tell a story” kind of questions. So they also want to

see that you can storytell with data and create slides.

Kirill: Okay, gotcha. And that’s for an operations management

position. I think it might be a bit different scenario for

different positions because you have marketing and stuff like

that, social people as well.

Josh: Yeah, for most of the Operations Org, I think it’s the same

test, but then when you get into the data science it’s a lot

more intensive.

Kirill: Yeah. Okay, cool. So now you passed those interviews and

then you went to work at Uber?

Josh: Yeah.

Kirill: Okay, gotcha. And you’re an operations manager right now.

What is your—you shared it with me before the podcast—

your goal for the next year or two?

Josh: Yeah, I’ve slowly been building up my analytics toolbox and I

really would love to become a data scientist within the next

year or two. I work very heavily right now in SQL and R and

I think I have a lot of the toolset already down, I’m just

trying to hammer down those final gaps in my experience.

Kirill: Okay, gotcha. So, as we can all imagine, Uber is an

interesting company from a data scientist perspective

because it’s all about data. They don’t actually have the

assets. They don’t own the cars. The drivers, as far as I can

remember, they’re not direct employees of Uber, they’re

contractors or something like that. The company wouldn’t

exist without the data. Would you say that’s a fair

statement?

Josh: Absolutely. It’s a completely data-driven company.

Kirill: Yeah, exactly. What would you say is the most exciting and

interesting part about Uber and its data?

Josh: For me it’s probably the fact that executives are bought in on

the data point of it. You know, a lot of companies—I used to

work for Caesar’s, they’re a Fortune 500 company, they’ve

been around for 60 years and they don’t have a strong data-

driven culture, so a lot of executives would make decisions

just based on their hunch or just based on their experience,

versus Uber, where data really drives all the decisions that

we make. So even if you are a lowly data analyst, if you find

something incredible in the data, you could probably pitch it

to somebody high up and turn it into a business outcome.

So that’s really exciting.

Kirill: Do you think that more companies should adopt that

approach?

Josh: Absolutely. I think we’re seeing that, you know, with tools

like Tableau that are more user-friendly and easier to deploy

dashboarding across your entire company, we’re seeing the

industry go that way. But I definitely think any major

company nowadays should be using data.

Kirill: Yeah, I totally agree. It’s just the world we live in. There’s so

much data all over the place and everybody is generating it.

You have to be conscious of that. And I wanted to ask you as

well, you worked both at Apple and at Uber. Not many

people get the opportunity to do both. I understand this is

not going to be a general life comparison, but from your

experience, which of these companies is more attuned to

their data?

Josh: My experience at Apple didn’t really give me a good enough

insight to say that it’s less tuned than Uber just because I

was in the retail organization doing sales. I wasn’t working

with data directly, but Apple is objectively the most valuable

company in the world. They have the best products, they're

incredible on all fronts, so I definitely wouldn’t make the

assumption that they’re not very data-driven as well.

Kirill: Yeah. So, they’re both basically leading companies in that

space. And it’s good that they’re in separate markets, they’re

not really competing with each other so there’s no problem

there.

Josh: Yeah, exactly.

Kirill: Okay. That’s pretty cool. And like probably a lot of listeners

are wondering this, and it would be unfair of me not to ask

you this question. I just wanted to ask you about the culture

at Uber. We’ve been hearing lots of stories in the news and

stuff like that. How do you feel about the culture at Uber

right now and is it something that you’re enjoying? How is

the work going there?

Josh: Yeah, I honestly can’t really say too much about what the

accusations have been. What I can say is that my personal

experience has been nothing less than phenomenal. I’ve

been there for almost a year and a half. I personally never

saw any of the issues that people say in the news. I’m really

excited about our new CEO Dara, he’s incredibly down to

Earth, incredibly smart and outgoing. In his first public

address to our company, I think I can speak for everybody

and say we’re all extremely confident in the future under

him. I think it’s probably the best time to be at this company

right now because if there were problems with the culture,

we’ve pretty much tackled a lot of it and it’s a really great

place to work right now.

Kirill: Fantastic! I’m very excited for you, man. That’s good to hear.

It’s always important to be confident in the place where you

work and where everything’s going. I wanted to move on a

little bit to how you’re growing. Obviously you’ve achieved

quite a lot in life already. You’ve jumped from magician to

music to finance and now Uber, but you still have goals and

ambitions and you want to become a data scientist, as you

said, in the next couple of years. What exactly are you

studying? You’ve mentioned a couple of softwares. What are

you studying and how are you going about it?

Josh: Yeah. Right now, one thing I’ve tried to do—in the past six

months, I challenged myself to learn R. And the way that I

did that was I essentially told myself, “Anything that you’re

thinking of doing in SQL, just try and do that in R first.” I

got rather good at data manipulation, not so much like

scripting and writing functions, but I got really good at data

manipulation first so now I’m trying to turn that into writing

functions and scripting side. One area where I know I lack

the next level skills to become a data scientist is my actual

statistics knowledge. I actually purchased one of your

courses, the business statistics one you have.

Kirill: Oh, cool. Thanks. That’s so cool. That’s the recent one.

Josh: Yeah, I’ve been going through it. I try and set time every

single morning. I wake up pretty early, at about 6:00 A.M.

and I try and get at least one or two hours of studying or

personal development time in the mornings before I go to

work.

Kirill: Nice. That’s really cool. So what do you think of the statistics

course so far?

Josh: So far it’s great. The thing is I know I’m decent at statistics, I

remember pretty much everything that I went through in

university, but it’s just applying it to a practical environment

is where I need to really hone in. For me, the challenge is

translating it from an academic environment to a practical

environment.

Kirill: Yeah. I figure that’s usually the case, especially—you know,

for me, because I also studied statistics at university, I

studied at high school and then I studied at university. And

then I remember it and I forget it. Literally a year later, I

don’t even remember what a p-value is. And then I figure

that if you embed those exercises, if you go through those

practical exercises that show you what it’s like, at least that

will give you something to remember in the future, “Oh,

yeah, that’s how I apply the p-value to this business

problem.” It’ll help anchor it in your memory. That’s why

this course, as you’ve probably noticed, has a few—like, after

every section there is an actual practical exercise on how to

apply it in a business sense and hopefully that helps

reiterate the knowledge.

Josh: Yeah, it definitely does. For me, if I can narrow down what’s

challenging, if you have a normal distribution in your data –

great, a lot of the stuff you learn applies perfectly. But it’s

when you have real life data that’s not normally distributed,

that’s messy, that doesn’t give you sample sizes for A/B

tests, stuff like that is when it gets challenging.

Kirill: Yeah, what do you need to do then? Okay, gotcha. And did

you study R because they use it at Uber or is it something

that you’re just doing for yourself?

Josh: I started with both R and Python and I knew that those were

the two languages that you should know as a data scientist.

And R clicked a little more quickly with me, so that’s the one

I went running with. I still don’t know Python. That’s

probably something that down the road I’d like to get more

comfortable at because I know you should know both, at

least to some degree. And yes, it did help. A lot of my co-

workers use R so I had a lot of example code I could go

through to do it. We have tools built already for R that

integrate with our databases and stuff like that.

Kirill: That’s cool. But at the same time, it wasn’t compulsory for

you to learn R. It was something that you went over and

above in order to get closer to that goal of yours of becoming

a data scientist?

Josh: I’d say it was both. Yes, it was absolutely that, I wanted to go

towards my goal, but I also ran into the problem where

sometimes your datasets get too big for SQL or Excel. So I

was kind of forced as well, but it was a nice push into

something new.

Kirill: Yeah, it happened naturally, gotcha. Okay, what about other

tools? What else are you exploring? You mentioned statistics

and R. Anything else?

Josh: I’m always trying to continue my SQL skills. I feel very

strong in SQL, though. Additionally, a lot that comes with

this is building good business foundations as well, general

good project management skills, because in my experience of

working as a data scientist, you have a lot of people who are

incredibly smart, incredibly academic, incredibly technical,

but they don’t necessarily have the project management or

interpersonal communication or business acumen. So for

me, it’s trying to be technical and build those technical skills

while at the same time remaining a really strong project

manager and storyteller and have good business acumen.

Kirill: Yeah, gotcha. And out of curiosity, I’m just wondering what

made you initially think about data science? What is the

reason or the factor that’s influencing you to be so

passionate about this field and wanting to learn more and

more? Because as we can already see from things that you’re

describing, it takes quite a lot of effort to get to the level that

Uber requires from a data scientist. What’s your motivator

behind this?

Josh: Truthfully, I’ve always just been pulled to data analysis. It’s

always been incredibly interesting to me. Any time I run into

a wall with not knowing how to do something in R or not

knowing how to do something in SQL, that’s the point in

which you learn the best, when you have to go searching for

an answer. And I just naturally gravitate towards trying to

learn more when I reach those situations. And at some point

in my development I just realized, “I’m naturally interested

in data analysis and data. Why not just pursue this?” I just

went headfirst and I haven’t looked back.

Kirill: Gotcha. And what has been your biggest challenge? In your

learning journey and your learning experience, what’s been

the biggest roadblock or challenge that you had to

overcome?

Josh: I would say probably working with people who have much

stronger pedigrees than myself. I went to UNLV in Vegas, it’s

not really a top tier school by any means, and I find myself

working every day with people who went to MIT or Stanford

or Harvard, and it does get intimidating. And for me, one of

the challenges has been talking to these people in a way that

they expect their colleagues to be. So, I felt like I’ve been up-

levelled from day one just by working with these types of

people, but it’s been challenging the whole way.

Kirill: Yeah. That’s a really cool challenge to have. That’s awesome.

They say that you’re the average of the five people that you

hang out with most. And probably at the workplace, if

everybody around you is pulling you up and you’re aspiring

to be like them and learn from them, that’s a great thing,

right? It’s much better than if you’re already a level above

everybody else and there’s nothing for you to learn from

other people. I think that’s a good problem to have.

Josh: Yeah, I’ve been incredibly lucky to just consistently find

myself in those situations. I think you’re exactly right with

that.

Kirill: That’s cool. So, you’re pretty confident that you don’t need to

go back to university to become a data scientist, that you

can learn through your work experience and you can learn

through the resources that you find online? Is that about

right?

Josh: I really do, yeah. And it also helps that I’m in a company

where I can see exactly where I’m trying to go. That really

helps, being able to visualize and work with people who are

already in that capacity. I imagine it would be harder if I

were outside of an organization like that. But definitely, I’ve

learned more from self-training through online resources

than I did at university.

Kirill: All right, so it’s pretty interesting that you know where

you’re headed and where you want to go. Do you think that’s

aligned with where the whole field of data science is going?

Like, being at Uber, you would have visibility of lots of

different analytics applications and lots of different types of

data, myriads and myriads of data out there. What do you

think is going to happen in the world of data and where is

this all going? And is your trajectory aligned with that?

Josh: Yeah, that’s a great question. That’s something I think a lot

about, because if you read into all the current data science

articles and a lot of the new courses on Udemy that are

coming out – I think you even have a couple – they’re all

seemingly focused around machine learning and deep

learning and that’s something that sort of intimidates me

because I know that requires a higher level of technical

expertise to build those kinds of things. I know there are

some packages that you can use in R that make it a little bit

easier, but I think that’s somewhere where I want to

challenge myself to get more involved in that because I really

think that’s where the industry is going. It’s something that I

have no experience in currently, so that’s probably an area

where I need to challenge myself.

Kirill: Yeah, totally. That’s the next step. You mentioned you enjoy

working with Tableau. This is something that you do in your

free time, is that right?

Josh: Well, it’s something I used heavily at Caesar’s. They had

Tableau Server there. And I do use it in my free time, but

mainly just to go through courses or in a learning capacity.

It’s a fun piece of software to use because you get to

combine your visualizations with Excel logic and also SQL

logic at the same time.

Kirill: Was it hard for you to pick up Tableau?

Josh: I actually learned it pretty easily. A lot of it is drag and drop

and pretty intuitive, but I had some courses. I didn’t have

one of yours back when I learned Tableau, but I had a

similar course, so using something like that makes it a lot

easier to learn it. And then of course the biggest factor is

having a reason to use it. I learned it while I was at Caesar’s,

so it was like direct on-the-job training, something you can

learn and you can apply immediately and I think that’s very

valuable to learn anything new.

Kirill: Would you recommend Tableau as a visualization tool to

people who are looking for one?

Josh: It depends on how you mean ‘visualization.’ If you mean one

chart that’s very specific, probably not, but it’s a great

dashboarding tool for dashboards that you want updated on

a recurring basis, that you can essentially automate, that

you can link directly to your data source and have beautiful

visualizations. It’s perfect for that. But if you’re trying to

create one chart, like Excel or R is a little better for that, I

think.

Kirill: Gotcha. And there’s another think I wanted to ask you

about. You mentioned that recruiters reached out to you on

LinkedIn about Uber. Is that because you were posting

something on LinkedIn, or is that because you arrange your

profile in some sort of way? Are there any tips that you can

give to us in that space?

Josh: Yeah, I wasn’t posting about anything, but I’ve always aimed

to have a very filled out LinkedIn profile. I think it’s really

important in this day and age. I also partly got my Caesar’s

job because of my LinkedIn, and it’s a really good

opportunity to display your skills, display your resume. Like,

I have a research paper that I did in university posted on

there. I know that endorsements aren’t so important

anymore because everybody seems to just endorse everybody

now, but I think that they were probably helpful for me back

in the day. And then I have a few written recommendations

that I got at Apple that I think were probably helpful for me.

Kirill: Yeah, definitely. Especially coming from Apple, that’s a big

one. I feel like with recommendations you need a couple, but

you shouldn’t overdo it. I once came across this one profile

on LinkedIn, a person that had 110 written

recommendations.

Josh: Jeez!

Kirill: Yeah. (Laughs) That was crazy. I was like, “What is going on

there? That’s not normal.” But yeah, you’ve got to be very

explicit about your experience so people who are looking to

fill a role, they can see that you have specifically done those

things that they are after and then they’ll get in touch with

you.

Josh: One other thing. I think it’s also important to be responsive.

If you are going to use it as a tool to find a position—like,

when I got that message from Uber about the position, I

literally responded back probably within two or three

minutes. Maybe that was a bit jumping the gun, but I think

that you should aim to have a really high level of

responsiveness and communicate back to recruiters in the

same level of language that you should be doing so.

Kirill: Yeah, I totally agree. And it’s a similar story for me. When I

was looking to leave Deloitte, I became more active on

LinkedIn, I fixed up my profile and so on, and then I was

posting stuff and people would message me sometimes,

rarely, but what I was actually doing, I got a paid profile and

then I could see people who looked at my profile, and I

would look at people who looked at my profile, and if they’re

even a little bit interesting to me as in they’re a manager, or

they’re somebody I could potentially get a job from, I would

just message them and I’d be like, “Hey, I noticed you looked

at my profile. Is there anything I can help you with?”

One of those people was a recruiter and I remember he

didn’t even have a photo on his LinkedIn, but he just looked

at mine briefly, I messaged him, and that was the recruiter

that got me the next job. So, you don’t only need to be very

quick at reacting. You also need to be very quick at being

proactive. Like, every day checking who has looked at your

profile and getting in touch with them. That’s one of the tips

that I can give on that space.

Josh: Absolutely. And when you’re being proactive, I think also the

LinkedIn message to the recruiter is nowadays a cover letter.

So, take what you would have done in the cover letter and

use that as a message to a recruiter and that might work.

Kirill: Exactly. And are there any other forums or social platforms

that you are quite active on? Like, maybe Tableau. Do you

visit the Tableau user group sometimes?

Josh: I used to look at the user-built dashboards, but I’m honestly

not very active on those.

Kirill: Okay. Yeah, with Uber it would be taking up a lot of your

time. I heard working there is pretty hectic.

Josh: Yeah, it’s a lot of hours, but I’m not bored. I never at the end

of the day say, “Oh, man, I’ve got to work more hours. I hate

this!” I never once said that. Hours are fine if you’re

passionate about what you’re doing, and we’re solving really

hard, impactful problems and happy doing it.

Kirill: You know what they say about consulting. Consultants on

average last about two years and that’s because they just

burn out. They’re passionate and excited about what they’re

doing, but it just takes up so much of their time and they’re

still so passionate. It’s like a fire that’s burning super-hot,

super-fast, super-strong – it quickly runs out of resources.

How do you feel about that? Do you feel that is an issue for

you, that’s something that might happen, or do you feel that

you have structured your work at Uber in such a way that

you still have time for your social life, you still have time for

hobbies and you still have a life and you won’t burn out at

some point?

Josh: I definitely still have a life. You know, we work a lot of hours,

but it’s not so much that it’s destroying my life. I honestly

did work more hours back at Caesar’s. It was more an

investment banking type culture. You know, we would have

people working from 8:00 A.M. till 2:00 A.M. and I’ve never

had a day like that at Uber. It’s been hectic, but it’s never

been that hectic.

But I think what you said about consulting is interesting

and I hear that from a lot of consultants. I work with a lot of

people who are ex-consultants, and I think there’s one key

difference that’s important to recognize. Consultants don’t

necessarily get to see the fruit of their labours. So they could

do all this work to pitch a solution to a company and then

the company would never implement it; or if they do

implement it, you are not a part of the team that implements

it necessarily. I think that’s a key difference because you

might think that your work is impactful, but if it’s never

actually being implemented or you’re never seeing it come to

life, that’s a key piece of this feedback loop that you need at

work that you’re missing out on. So I think you might be

more inclined to get stressed out easier if you’re stuck in

this situation where you feel like you’re not doing something

meaningful.

Kirill: Gotcha. That’s a big one, yeah. I think I felt the same thing.

You can implement something and then it’s even in the news

a few months later but it’s like, “This company did that,” and

not only nobody knows that your team was part of this

process, but you don’t even know how they finished it off or

did they do it right and things like that.

Josh: Yeah. Or even back at Caesar’s, we would work until

midnight or 1:00 A.M. on a deck that would go to the CEO of

the company. Sometimes we would build this deck and then

it would just get scrapped, like, “Oh, yeah, we decided not to

do that.” And that feels very different than if the deck

actually did go to the CEO and they decided to purchase a

company because of it. You know, those are very different

outcomes and your stress level will probably be different

depending on which one would happen.

Kirill: Yeah, exactly. By the way, for those listening, by ‘deck’ we

mean—I think it’s a consulting term, it’s a deck of

PowerPoint slides.

Josh: Yeah.

Kirill: And a similar thing I heard about big companies like

Facebook and Google—no offence to anybody, especially if

somebody is from those companies listening, I totally admire

the amount of work they put in and the amount of effort and

the talent that works with those companies, but what I was

going to say is that I’ve heard that the way sometimes

companies of that magnitude, that they can afford to attract

talent by just throwing money at people so they can afford to

pay double or triple the average salary in that space, which

is great.

But then for Google, around 80% of the projects that they

work on never actually see the light of day because there’s a

lot of pilots, there’s a lot of tests and there’s a lot of ideas

that they work on, and people are coding away, developing

these tools and really cool things that might change the

world like Gmail. That never existed 15-20 years ago. That’s

a product of Google, that’s one of those things that did see

the light of day.

But there’s hundreds and thousands of other projects that

they do that never see the light of day. So it’s the same

problem, right? You might be working away for a few years

on a project, coding your life away every day, and then it just

never gets off the ground. Now how would that feel? That

wouldn’t feel good, would it?

Josh: No, it wouldn’t. I think there’s something there, though, too.

It’s like if you’re starting a company. There’s two parts of it:

there’s how good is the actual idea, but then there’s how well

did you implement it? There’s some percentage of those

ideas that maybe just weren’t implemented well enough.

Maybe they didn’t have the right project manager or they

didn’t have the right team working together. So I think it’s

also important to remember that a lot of ideas at a company

might turn into nothing, but it could be a result of you also

deciding it wasn’t worth it. But you’re absolutely right, there

are many different courses of action that your time and

effort goes into that doesn’t do anything.

Kirill: Yeah. And to your point about ideas, there’s so many ideas

around the world and lots of people actually have these

ideas and that’s fantastic, but an idea is nothing without

implementation. If you have an idea, that’s cool. You know,

somebody might have had an idea for electricity, but if they

hadn’t gone through the efforts of researching and

understanding and making it happen, we wouldn’t have

electricity now.

With ideas, you always need a person with an idea and a

person who’s able to execute. If you put those two together,

then you get a successful company, or if one person has

both inside them, which is very rare. But I’ve got a feeling

that there’s a lot of people with ideas but not enough people

who can just sit down and execute that job, so there’s space

for both. For those listening out there, decide for yourself

who are you. Are you a person of ideas, which is good and

it’s very trendy and fashionable to be the person who is

coming up with ideas and creating new businesses and so

on, but there’s always a second part to it.

Every business that’s successful out there from Airbnb to

Uber to Microsoft to all these other ones, there is always

somebody in there who is doing the execution, who is sitting

down, who is putting in the hours and who can get things

done. It’s very important to also be a person like that or have

a person like that who can get things done. So, if you’re not

a person with ideas, that’s not a problem at all. Just be a

person who can get things done and you’ll be as valuable as

a person with ideas, if not more.

Josh: Yeah, exactly. To that, when I decided to first study finance,

I always had in my mind that the whole reason I’m studying

business and getting into this field is because I’m not

necessarily an idea guy, but I want to find an idea guy and

work with them. I wanted to learn the business side of it and

the finance side of it and be able to help somebody who

doesn’t have business acumen turn an idea into a business.

Kirill: Yeah, and those skills are very valuable. You’ve often seen

this is the case. A person with an idea might have one idea –

and it’s great when they have lots of ideas and then they

know how to implement them or they have the right

partnership where somebody is implementing them and then

they move on to the next idea. But a lot of times, the person

with an idea will get so stuck on their one idea, and then if it

doesn’t lift, if it doesn’t get off the ground, they will never

move on to something new. They will just really adamantly

believe in that and never change their opinion.

Whereas the person who can get things done can work on

one idea, they can work on another – it’s a very transferrable

skill, you know, you go in and you’re like a CEO or an

operations officer or a director or something. You get things

done here, you get things done there. It’s very transferrable

and that’s why it’s also a very valuable skill to have. Like

you say, if you want to find a person with an idea, I’m pretty

sure if you keep going the way you’re going, that person with

an idea will find you, many of them will find you, and you’ll

be like, “Okay, which one do I want to work with now?”

Josh: Yeah, absolutely. I just want to remain flexible so that when

I meet the right person at the right time, you know, I’m not

in a position where we can’t pursue that idea. I would say

everybody should always try to remain flexible because you

never know what opportunity might pop up like Uber did for

me.

Kirill: Yeah, exactly. Opportunities come and you’ve got to grab

them. What’s that saying, that luck is when opportunity

meets preparation, right? You’ve got to be prepared and then

opportunity will come and that’s the definition of luck,

according to some people. Well, that’s a good segue. Thanks

a lot, Josh, for coming on the show. How can our listeners

and maybe those people with ideas contact you and find out

how your career is going?

Josh. Yeah, absolutely. They could message me on LinkedIn.

That’s probably the best way. Like you heard about me

talking to the Uber recruiters, I’m very responsive, I love

chatting to people on there about anything and everything.

That’s probably the best way.

Kirill: Gotcha. I’ve got one more question for you today. What’s a

book that you could recommend to our listeners so that they

can better themselves?

Josh: One book that comes back to what I was talking about

earlier with statistics, transferring statistic knowledge from

academic to practical, there’s a publisher called O’Reilly that

makes all these technical books. They have one called

“Practical Statistics for Data Scientists,” and it does an

incredible job of doing exactly what I mentioned I have

trouble with and that’s translating it to a practical

environment. And they do it in a manner where they use R

and they show you the R code directly and they have sample

datasets. I would highly recommend that book.

Kirill: Fantastic. Thanks a lot. So, that’s “Practical Statistics for

Data Scientists” by O’Reilly. Thanks again, Josh. Great chat,

I really loved talking about the whole entrepreneurship and

things like that. Thanks a lot for coming on the show, man.

Josh: Absolutely. Thank you for having me and thanks for the

Tableau conference as well.

Kirill: No worries. Enjoy that. See you.

Josh: See you, Kirill.

Kirill: So there you have it. That was regional operations manager

at Uber, Josh Kennedy, and also the winner of our

SuperDataScience giveaway. I hope you enjoyed this

episode, it was very interesting. Unfortunately, we couldn’t

go into a lot of technical stuff because working for a

company like Uber, you use a lot of sensitive information

and Josh had to be very careful about what he can say and

can’t say and we obviously respect that, but at the same

time we had some interesting conversations, especially

around the space of entrepreneurship and ideas.

And my personal favourite part was probably the whole

philosophy that Josh has that even though he’s already at

Uber and he’s already got a very interesting, exciting role, he

doesn’t want to stop there, he wants to keep going, he wants

to keep going within the company, within Uber, he wants to

become a data scientist, and he’s doing lots of things

towards that aspiration like, for example, waking up at 6:00

A.M. every day to study some things before he goes to work.

You’ve got to have a lot of drive and motivation to do that

and that’s very inspiring when you look at that. A lot of time

people say, “I don’t have the time. I don’t know when to fit it

in. I’m very tired when I come back.”

Well, there’s always some time to find. There’s a saying that

nobody is short for time, it’s just a matter of priority. If

you’re not getting something into your day, that means it’s

not just because you don’t have enough time, but maybe it’s

not a priority in your life. That can be fair enough in lots of

cases, but if you really, really want something, then you

should make it a priority like Josh, who really wants to

become a data scientist. He made it a priority and he’s

working towards that, which is very admirable.

So there you go. I hope you enjoyed this episode. You can

find the show notes and the link to connect with Josh on

LinkedIn at www.superdatascience.com/95. We’re getting

very close to episode number 100. There, as well, at that link

you can find the book that Josh recommended as well as the

transcript for this episode. And I look forward to seeing you

here next time. Until then, happy analyzing.