Ask HN: Can the “Who is Hiring?” post include a bit about the interview process? • Hacker News Board

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#51

Post by 3pt14159 » Sat, Apr 30, 2016, 12:01 PM UTC

crdb wrote: post #49

marmaduke wrote: post #46

Earlier quoted context omitted.

Ah we usually call them outliers and use robust techniques or not-L2 stats when they are pervasive in the data. Still, in my experience, handling outliers is an application dependent thing, as they may be benign or they may suggest another stat model entirely. Otoh, I agree not being aware of over fitting is definitely grounds for setting aside a candidate for ML job.

There's a difference. Imagine a simple one dimensional linear regression. A value with x close to the mean, but extremely high y would barely move the line as a whole up or down as you vary y. The gradient would not be much affected. A value with extremely high x does not need to move much to change the gradient of the line. You might even change the sign of the gradient. Both are outliers but the second has higher l…

Do you mind if I ask you where you work? I find most people practising "machine learning" have barely gotten past kmeans, naive bayes, and SVMs with very little actual understanding on how or why they work and where they fall apart.

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#52

Post by mappy » Sat, Apr 30, 2016, 12:15 PM UTC

llamataboot wrote: post #6

I wish companies didn't think their interviews were some weird "secret sauce" -- I've had companies flat out refuse to tell me what the interview process would be like, or even how long I should expect for the interview beyond "1-4 hours". Well, you know 1 hour is a lot different than 4 hours! Personally I think all companies should be using pair-programming or contract to hire, as I think trivia questions and whiteb…

> Personally I think all companies should be using pair-programming or contract to hire

You should qualify that with "all companies by which I want to be hired", because not all teams/developers pair program or want to pair program.

The team I'm on does a phone tech interview, then an in-person interview where we dig into history, then a mix of problem solving, pseudocode problems, OO/schema design, and web app design/technologies/approach, and then more interviews with the extended team. While we will sit with each other to help out at times, sometimes for hours, we don't strictly pair- that is just when help is needed. We rely on some up-front design and all PR's code reviewed for quality control, in addition to QA and approval by application owner.

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#53

Post by crdb » Sat, Apr 30, 2016, 12:29 PM UTC

3pt14159 wrote: post #51

crdb wrote: post #49

Earlier quoted context omitted.

There's a difference. Imagine a simple one dimensional linear regression. A value with x close to the mean, but extremely high y would barely move the line as a whole up or down as you vary y. The gradient would not be much affected. A value with extremely high x does not need to move much to change the gradient of the line. You might even change the sign of the gradient. Both are outliers but the second has higher l…

Do you mind if I ask you where you work? I find most people practising "machine learning" have barely gotten past kmeans, naive bayes, and SVMs with very little actual understanding on how or why they work and where they fall apart.

I run my own data consulting firm based in Asia.

Originally, we were going to build high dimensional statistical learning systems crunching large datasets on GPUs in Haskell.

90% of clients cannot feed me the data, so I end up building them a data warehouse first; in some cases we even redo their data model. 100% of clients have datasets too small to justify getting out of R and single CPUs, so our Haskell ML libraries are, so far, on the wishlist only (I think Tweag has had more success there, but I still have feeble hope that one day...) Hence the RM focus as well as ML. The ML side is sort of picking up this month.

That being said, I'm not actually that well versed in ML. Just the guy running the company. I've built (and read) just enough to know how it works, how it applies to clients and who to hire to get the job done properly...

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#54

Post by cripesmarcy » Sat, Apr 30, 2016, 12:46 PM UTC

gaza3g wrote: post #2

This is a great idea. I've been in many interviews where I thought I did pretty well only to be told, "oh, this is just the first of many interviews". I wouldn't have applied if I had known since every onsite interview requires me to at least take half a day off from work. That is time that can be used for something else. But I do have to mention that with the Big4, they will let you know in detail about the whole pr…

I agree, it's pretty frustrating when that happens. Especially when you take time to travel for the interview only to find out that it is the "first of many."

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#55

Post by kevindeasis » Sat, Apr 30, 2016, 12:47 PM UTC

What is your guys' go-to strategy in getting an interview?

Especially, if you are a recent grad in Canada (AB) how do you get more job interviews? Especially for top tech companies?

Like how do you arrange your resume so it passes the key word scan.

Who do you pass your resume to?

Which websites should you go to?

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#56

Post by salarynope » Sat, Apr 30, 2016, 1:17 PM UTC

JDiculous wrote: post #17

Before even that, I'd rather see salaries posted. Only a disappointingly small number of companies post salary information.

In my company, it's very rare that we'll have a need that's so specific that we could actually know the salary within $10k before we hire.

It's far more common that we have openings for "Software Engineers", and we end up hiring one very junior, one very senior engineer, and some folks in between. Thus, from the same ad, compensation could range from $90k w/1,000 shares to $280k w/20,000 shares. And, frankly, saying "salary is typically between $75k and $300k" isn't useful information.

How our comp actually works is that at some point in the interview process, you tell us how much you're hoping to make, and then we set the bar appropriately. If you want $250k, the bar will be very high. If you want $100k, it will be substantially lower.

There is no reason to be "disappointed" by it.

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#57

Post by typon » Sat, Apr 30, 2016, 1:30 PM UTC

crdb wrote: post #53

3pt14159 wrote: post #51

Earlier quoted context omitted.

Do you mind if I ask you where you work? I find most people practising "machine learning" have barely gotten past kmeans, naive bayes, and SVMs with very little actual understanding on how or why they work and where they fall apart.

I run my own data consulting firm based in Asia. Originally, we were going to build high dimensional statistical learning systems crunching large datasets on GPUs in Haskell. 90% of clients cannot feed me the data, so I end up building them a data warehouse first; in some cases we even redo their data model. 100% of clients have datasets too small to justify getting out of R and single CPUs, so our Haskell ML librari…

I think what maybe tripping people here is your use of the word machine learning. Personally, as you're using it is how it should actually be used: applied statistics. However, a lot of people think of machine learning as a collection of algorithms they can use to make predictions about some given dataset. Use sklearn to model.fit(xtrain, ytrain) and model.train(xtest, ytest). I personally blame Coursera and the online courses for this trend.

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#58

Post by dominotw » Sat, Apr 30, 2016, 1:49 PM UTC

noarchy wrote: post #26

If I could blacklist companies that do whiteboard interviews, for example, I'd do it. I'm not expecting most companies to show their hand, though, precisely because of how unpopular these practices have become.

> precisely because of how unpopular these practices have become.

I've been interviewing for past 1 month and every single company made me do whiteboard, big O stuff past phonescreen.

I think you are over estimating how much HN leaks into real world.

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#59

Post by thedufer » Sat, Apr 30, 2016, 1:53 PM UTC

eric-hu wrote: post #36

imh wrote: post #25

Earlier quoted context omitted.

I think a part of the secrecy is so that if it goes poorly they can stop the interview after a really bad session without indicating to the candidate that it's gone so badly. "Yup, it's always just two sessions, goodbye." This is an actual rational I've heard. I don't agree with it, but it's a thing.

For anyone who finds this to be a plausible reason, I did too. Then I realized that a more transparent company would simply tell me that I they're cutting the interview short.

There's a comfort advantage to both parties if you do rejection over phone/email instead of in your office, in my experience.

Also, I've seen interviews cut short for both extremes (going really well and going really poorly) so it's easy to give the wrong impression that way.

Re: Ask HN: Can the “Who is Hiring?” post include a bit about the interview process?

#60

Post by marmaduke » Sat, Apr 30, 2016, 1:55 PM UTC

crdb wrote: post #53

3pt14159 wrote: post #51

Earlier quoted context omitted.

Do you mind if I ask you where you work? I find most people practising "machine learning" have barely gotten past kmeans, naive bayes, and SVMs with very little actual understanding on how or why they work and where they fall apart.

I run my own data consulting firm based in Asia. Originally, we were going to build high dimensional statistical learning systems crunching large datasets on GPUs in Haskell. 90% of clients cannot feed me the data, so I end up building them a data warehouse first; in some cases we even redo their data model. 100% of clients have datasets too small to justify getting out of R and single CPUs, so our Haskell ML librari…

Do you ever have the impression that the model you are going to apply influences how you clean the data? What happens then when you redo the model?