SDS 095: From Uber to Data Science – A Winner’s Journey - SuperDataScience - Big Data | Analytics Careers | Mentors | Success

SDS 095: From Uber to Data Science – A Winner’s Journey

Welcome to episode #095 of the Super Data Science Podcast. Here we go!

Today's guest is Regional Operations Manager at Uber, Josh Kennedy

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From magic to music, to finance to Uber and data science, Josh Kennedy knows a thing or two about winning. And win he did – the SuperDataScience giveaway saw him walk away with a ticket to this week's Tableau Conference in Las Vegas.

You will be inspired when Josh tells you about how he got here, his learning regime, the ideas behind the choices he makes, and just his approach to seizing opportunity in general.

Along the way, we also discuss entrepreneurship, leadership, and career goals for a full-on value-packed episode.

Tune in now!

In this episode you will learn:

  • What it's Like to Work at Uber (11:12)
  • Continuing to Learn: Hard Skills and Soft Skills (15:32)
  • Learning Tableau, When Tableau is the Right Tool for the Job and When it is Not (25:27)
  • Tips on Optimizing LinkedIn (27:20)
  • The Importance of Job Satisfaction/Quality of Life (31:01)
  • The Role of Ideas vs. Execution (36:04)

Items mentioned in this podcast:

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Episode Transcript

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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.

Kirill Eremenko
Kirill Eremenko

I’m a Data Scientist and Entrepreneur. I also teach Data Science Online and host the SDS podcast where I interview some of the most inspiring Data Scientists from all around the world. I am passionate about bringing Data Science and Analytics to the world!

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