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I had concerns earlier this year when I interviewed at WeWork—which was the worst interview experience I’ve ever had. I applied for a data science role. The fir
by cgearhart 7y ago
I had concerns earlier this year when I interviewed at WeWork—which was the worst interview experience I’ve ever had. I applied for a data science role. The first two hours of the on-site were painful—they seemed to be asking questions tailored to be outside my experience. The third interviewer came into the room and said, “I, uh, just looked at your resume and I have to ask, why do you want to be a backend engineer?” :facepalm: I showed him my application for a DS role, so he left and came back with a DS guy who made up an interview on the spot. I (fortunately?) didn’t get a call back.
- metalliqaz 7y agoWeWork is basically a real estate company. Why would they need a data science engineer?
- LargeWu 7y agoBecause they are cosplaying as a tech company.
- metalliqaz 7y agoI guess that's how you get those SoftBank billions.
- hef19898 7y agoOnly thing missing is a plan to get as much of these billions out of the company into your own pocket then, I guess. Not that stupid from a purely self-serving perspective. Ignores every aspect of corporate governance and business ethics, so. Not that SoftBank seems to care if they can get an IPO.
- Wellrowed 7y agoThe email I received after applying for a job many months ago: “Thanks so much for taking the time and interest in applying to WeWork Global Technology. Your application has been received and we will review it as soon as possible. Once we've had a chance to review we'll be in touch on possible next steps, thanks again for the time! Regards, WeWork Global Technology”
- rm_-rf_slash 7y agoMy guess is to model the supply of available real estate and demand for scalable office space and then optimize their leases accordingly.
- luckydata 7y agoit's more about facilities management. Collecting data about who (and how many) go in and out the doors, who's where when to optimize things like heating or air conditioning, meeting room occupancy etc... I have a friend working on their data platform and the concept is pretty cool, I can see if I was managing an office I would want that data but the rest of the business is just awful.
- aaronbrethorst 7y agoHow else would they be able to determine that people like to drink coffee in the morning? https://twitter.com/modestproposal1/status/1085583434788020227?lang=en https://twitter.com/modestproposal1/status/10855834347880202...
- RandallBrown 7y agoI mean, that's not what the writing said at all. The data said that the line for coffee was too long, so they hired a barista to help out with the line.
- aaronbrethorst 7y agoI’m exaggerating for comedic effect.
- mrguyorama 7y agoI think the tweet is really pointing out that offices all over the world have managed and figured those things out without building out a complex sensor network and platform for 50 years.
- cgearhart 7y agoFrom what I understand they wanted to instrument their offices (with cameras, microphones, thermometers, etc.) to collect data on the occupants ostensibly because they’re trying to be a tech company. Felt Orwellian, but it sounded interesting enough to at least hear them out.
- dictum 7y agoNot that it's novel — there are corporations specialized in tools to monitor employee activity — but there's no bamboozling in that claim: monitoring nearly every activity, no matter how intrusive, is what almost software and hardware does now.
- orblivion 7y agoOn the one hand it seems like a new level of creepy. On another level, it's kind of funny to have tech companies be the ones getting spied on.
- TrackerFF 7y agoAt my old company (energy company), they've now installed sensors at every desk - to track whether or not someone is sitting at the desk, and their activity level.
- adrr 7y agoData allows people to make more informed decisions. You don’t need to be a tech company to benefit from a data science department.
- onlyrealcuzzo 7y agoYou do need data, though. And if you don't have a lot of customers, or a lot of skus, or a lot of transactions -- you probably don't have a lot of data.
- adrr 7y agoI assume we work spends tens of millions on marketing that could benefit from optimizations through data science.
- nerfhammer 7y agoto be fair "data scientist" means different things to different companies, and for some may be just synonymous with "business analyst" but sounds cooler
- mandeepj 7y ago> WeWork is basically a real estate company. Why would they need a data science engineer? data science is a tech agnostic role. Wework might want to play with various data models for predictive modeling.
- dehrmann 7y agoEngineer? Harder to say. Data scientist--that's easy. Stackbucks is very good at looking at demographic data and recognizing where future demand will be new new locations. They basically mark gentrification.
- kevin_thibedeau 7y agoStarbucks has a long list of failed stores. They aren't that good at picking locations. They just saturate and keep what doesn't lose money.
- bduerst 7y agoHistorically Starbucks has been used as a market indicator for other companies' expansion. If a starbucks opened in a location then it was assumed that there were growth factors at play in the market since that was the north star for Starbucks. Starbucks in 2019 is the McDonald's of coffee shops, so it's not the same, but if you track their Starbucks Reserve locations you'll find the same predictions being used.
- cure 7y agoThe NYC Starbucks Reserve location is certainly in a hot spot, right next to the Google offices and Chelsea Market.
- patio11 7y agoDo you work in commercial real estate? My father does, and would pick them and Walgreens as the most effective scaled siting operations in the US. Optimizing for absence of failed stores would be an interesting utility function for them to have, but since they own substantially all of the stores (and therefore don't have franchisee relationships to consider, where volatility for a partner might impact you disproportionately to economic loss), that would be a suboptimal utility function. They should calibrate their risk appetite to maximize profits; occasional failed stores are just a search cost.
- 7y ago
- komali2 7y agoI had a remarkably intense series of frontend... ish interviews for a really difficult to define project. As in, I was working very hard in the little 5 minute slices of time I got for "do you have any questions" figuring out just wtf the job was and what the team was doing, and nobody could really explain it. It was some sort of "connectivity and identification team" working to identify people/customers/tenants/whatever. Something like, you'd walk in, and WeWork would know it was you, and like, turn your office lights on or some shit. It was going to start off with keycards and I remember someone talking about bluetooth or wifi recognizing your phone, eventually doing face recognition. I couldn't figure out the point. A HUGE team. The questions I was being asked were wild system design questions and android app stuff (what? I'm frontend lol). All so that people's desks would be at a certain height or whatever when they came in the room.
- semi-extrinsic 7y agoThey were trying to find more secret sauce that's less expensive / more cheaply scalable than the Kombucha.
- mandevil 7y ago"WeWork used [a sensor network that tracked everyone throughout the building combined with machine learning] to learn that people drink coffee in the morning so they should hire a barista." Source: https://twitter.com/modestproposal1/status/1085583434788020227?lang=en https://twitter.com/modestproposal1/status/10855834347880202... Sounds like a reasonable use of tens of millions of dollars of VC money.
- coredog64 7y agoNot a fan of WeWork, but there actually is something to this. We have two coffee makers in the break room at work, and there's always a line. If they brought in a barista who could work the machines, it's theoretically possible that you'd get better efficiency as there wouldn't be the dance of "who is next in line" or "sorry, gotta block the machine while I get sugar" or "I just want some hot water". I'd love to be able to point building management at some data that says that a barista costs $100/hour for 2 hours, but having them would unlock $1000/hour in lost productivity.
- puranjay 7y agoAll dumb money needs some smart titles to keep attracting more dumb money
- samsonradu 7y agoIt also helps with the evaluation. Looks good on a pitch to investors.
- likpok 7y agoReal estate is a data play: figuring out which locations are going to be valuable. McDonalds famously does tons of research on locations, so much so that "be mcdonalds-adjacent" is an acceptable strategy. I'm not entirely sure what a data science engineer does, but somewhere between "making it easier for the DS team to find what they need to find" and "figuring out where we should buy/lease next".
- bduerst 7y agoPrecisely - Real estate boils down to financial operations on assets that have a number of factors and signals that go into predicting market prices. This also includes demand for commercial space.
- tgtweak 7y agoFrom what I heard they were doing some notable data engineering - leveraging 4square data to decide where to put locations based on optimisation algorithms, profiling potential lessees based on known good ones, optimizing workspace layout based on camera and keyfob data, lease price elasticity tests... Lots of interesting domains. Sadly I'm sure this was/is one of the first departments to get downsided post backdown.
- btown 7y agoData science is one of the few areas where WeWork may achieve an economy of scale - your local coworking operator won't be able to have that in house, and their ops system SaaS provider probably doesn't have the margins to invest heavily in it. If they're this messy at it though, that's not a good sign...
- ahi 7y agoExcept the local operator will have a more intimate understanding of area dynamics than data science can provide.
- notfromhere 7y agoBurger King's strategy for the longest time used to be 'just build across the street from McDonald's'
- tootie 7y agoWhy do taxi companies like Lyft and Uber need so many engineers? And why have they been utterly helpless to improve rider experience?
- AgloeDreams 7y agoI never felt it was so black and white as people make it which is part of WeWork's problem. WeWork's long game and eventual income is Real Estate, but their short game, their bread and butter, their brand, and their marketing is and always has been services and transactions. They compete much closer to a Starbucks than a Real Estate company but it's like neither side quite got it. (esp considering the CEO was a scam artist abusing the Real Estate side of the business while misdirecting everyone towards services) WeWork is (to most) a company whose focus was on people and atmosphere, and on service. I would argue that they are MUCH closer to a hospitality chain like Marriott than a Real Estate firm or a tech co.
- silasdavis 7y agoYes hospitality and they're pretty good at it as far as I cam tell.
- miguelmota 7y agoReal estate companies also need data science since they heavily rely on data for making decisions.
- megaremote 7y agoAre you kidding? Is there any industry that can not be helped by data science?
- barce 7y agoThe same reason a real estate company needs data science. To find correlations that no human can find given their vast stores of data for co-workers.
- theferalrobot 7y agoI had a similar experience a month or so back with a large consulting firm I was interviewing for in the DC area. It was also a data science role and they kept asking me webdev questions. In this case they knew it was for a data science role but I could also tell the guy hadn't a clue about most machine learning and data science topics. He was probably just as uncomfortable as I was. I didn't take the job.
- scottlegrand2 7y agoA friend interviewed there and they dismissed him as overqualified for DS.
- philliphaydon 7y agoHaha, I had an interview many years ago in Australia, was a full 2 hour technical interview in MS technologies. Nailed all the C#/.NET/SQL Server questions. Nailed everything they threw at me. I felt really proud of myself because I thought I was doing very well. After they were done with me I started asking questions. I asked what they would have me doing? "Oh the back-end system & api is done by a different team, you would just be doing the HTML/CSS for the front-end team" I was furious when I left...