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Some Reflections on Being Turned Down for a Lot of Data Science Jobs

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Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#141

Post by ploggingdev »

minimaxir wrote: post #22

Many recommend setting up an online portfolio for these types of positions. But I've applied to a number of Data Analyst/Scientist jobs recently and I am immediately rejected almost every time despite highlighting my blog/portfolio ( http://minimaxir.com ) and my GitHub with open-source code/Notebooks for each and every post ( https://github.com/minimaxir ), both of which have topped HN on occasion. Internal recruite…

I would suggest taking part in the Who wants to be hired monthly thread if you have not been doing that already.

I realize that most startups recruiting through HN are looking to hire for web, app or backend development, but there are a few data science jobs. Since people recognize you here on HN, you have a much better chance of landing a job.

It's unfortunate that most recruiters primarily screen based on resume.

I don't know if Triplebyte [1] helps people find data science jobs, but do check with them.

[1] https://triplebyte.com/

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#142

Post by mehaveaccount »

Bootvis wrote: post #57
jknoepfler wrote: post #52

Earlier quoted context omitted.

It's literally the first thing you learn in data science / machine learning coursework about evaluating model performance. It would probably be better to ask the candidate to whiteboard a set of metrics for evaluating model performance rather than ask for the definition of a pair of words, but the concept is practically the for-loop of data science. Edit: note that I'm not saying you need this to add roi as an analys…

I haven't taken a lot of data science classes but I'm not sure that's true. If you start with linear regression the mean squared error would make more sense. I actually searched through "The Elements of Statistical Learning" and the word 'recall' is not used in this sense at all.

People don't pay for linear regressions. They pay for discrete things: what is my best option among my three clear courses of action. Linear regression can be a tiny piece of a larger argument in favor or against one option or the other, but that alone doesn't make money.

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#143

Post by graphememes »

I don't have much Data Science job hunting experience, however I have applied to and been hunted by over 100 startups, 24 enterprise companies, and 12 large "startups".

I've had the following:

  - 106 Rejections
  - 39 Offers
  - 24 Refused
  - 15 Contemplated
  - 5 Taken
Roles Applied for:

  - Software Engineer (55rj, 8o, 6r)
  - Product Manager (5rj, 6o, 5r)
  - Senior Software Engineer (31rj, 23o, 22r)
  - Product Lead (0rj, 1o, 1r)
  - Senior Product Manager (9rj, 3o, 2r)
  - VP of E (2rj, 1o, 1r)
  - CTO (0rj, 1o, 0r)
It's been a journey. I don't keep an exact list so this is from looking at my calendar and doing some basic math. This certainly doesn't include all of the role changes within companies.

Things to note:

  - People conflate Agile & Scrum a lot.
  - Make it easy for people in the room to know what you personally accomplished during your career.
  - Make an impression, don't overdo it however.
  - Make your descriptions easy to understand.
  - Don't just list tech stacks on your resume, list achievements.
  - Stay consistent.
  - Ask questions.
Also Note:

Regardless how impressive your Github & Stackoverflow accounts might be, you will still be asked to do a stupid code challenge. It irks me. I understand the reasoning for it when you don't have a viable pool of information on the individual, but when you do... It's just disrespectful.

Few places I have been rejected by:

  Salesforce, Atlassian, Trello, Twitch, Segment, AirBnB, Twitter, OKCupid, LinkedIn, Shippo,  and many many more.
Some places I have been offered by:

  Amazon, VMWare, Oracle, Google (twice), Apple (twice), Venmo, Auth0, Discord, Youtube, Hitbox, Steam, Pusher, Cloudflare

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#144

Post by Bootvis »

mehaveaccount wrote: post #142
Bootvis wrote: post #57

Earlier quoted context omitted.

I haven't taken a lot of data science classes but I'm not sure that's true. If you start with linear regression the mean squared error would make more sense. I actually searched through "The Elements of Statistical Learning" and the word 'recall' is not used in this sense at all.

People don't pay for linear regressions. They pay for discrete things: what is my best option among my three clear courses of action. Linear regression can be a tiny piece of a larger argument in favor or against one option or the other, but that alone doesn't make money.

That's obvious but not at all what I responded to in my post.

I responded to the claim that ML courses start with the definition of precision and recall. In my admittedly limited experience those courses start with linear regression and mean squared errors. After that, there is so much generalization possible and that doesn't include precision/recall.

You make money by solving someone's problems, making money by stating definitions is only done on TV quizzes.

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#145

Post by kriro »

namelezz wrote: post #71
kafkaesq wrote: post #47

So you're at least occasionally getting actual feedback from some of these discussions. That's quite something, actually. BTW, as to some of that "feedback": Honestly, I think the way you communicated your thought process and results was confusing for some people in the room. "Okay, pal - let's put your people up in a room full of strangers (some of whom show through their body language and/or constant phone-checking…

> Honestly, I think the way you communicated your thought process and results was confusing for some people in the room. Wow, get similar rejection lately: this is a fast paced company and the way you explained your thought process was confusing and might slow us down, so good luck with your job search.

This sounds like a pretty douchy sort of "yeah you're just not good enough, look how fast we are" jab by them.

Better not answer with "Thank you very much. I also had a feeling that some people in the room lacked the mental capacity to follow my explanation."

;)

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#146

Post by cwilkes »

muninn_ wrote: post #24
minimaxir wrote: post #22

Many recommend setting up an online portfolio for these types of positions. But I've applied to a number of Data Analyst/Scientist jobs recently and I am immediately rejected almost every time despite highlighting my blog/portfolio ( http://minimaxir.com ) and my GitHub with open-source code/Notebooks for each and every post ( https://github.com/minimaxir ), both of which have topped HN on occasion. Internal recruite…

Yeah. The problem is recruiters are almost universally non-technical, so they can't properly gauge your talent nor do they understand the job requirements fully.

I wouldn't limit it to recruiters ... some engineers see the word "QA" or "SDET" and think the guy isn't worthy of being a "real" software engineer, or if they do then it is at the lowest rung of the ladder. Really annoying.

In the OP's case I would change their title (if applicable) to "QA / engineer" as a) that probably paints a more accurate picture of what you were doing and b) gets around yokels that look down on QA/SDET.

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#147

Post by cwilkes »

hudibras wrote: post #140
bsg75 wrote: post #55

> Quite honestly given your questions [about vacation policy] and the fact that you are considering other options, [we] may not be the best choice for you. Dodged a bullet on that one: - PTO is a touchy subject? - They are looking at more than one candidate, why would any candidate limit themselves to one potential employer?

Yeah, that's just weird. Paid time off is part of the total compensation package; it would be strange if a candidate didn't ask about it.

And if they are touchy about it probably also means that they won't pay it out if you leave ... that's the law in California but not in other states like Washington.

I was shocked to hear that, apparently it is somewhat common in retail jobs not to get paid out. Happened to me at a company that claimed to be more of a technology company. Maybe they don't think word gets around. Or that smarter employees will just take a lot of time off before quitting, which does a lot more harm to the company than if they just paid out the time owed to the employee.

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#148

Post by michaelscott »

graphememes wrote: post #143

I don't have much Data Science job hunting experience, however I have applied to and been hunted by over 100 startups, 24 enterprise companies, and 12 large "startups". I've had the following: - 106 Rejections - 39 Offers - 24 Refused - 15 Contemplated - 5 Taken Roles Applied for: - Software Engineer (55rj, 8o, 6r) - Product Manager (5rj, 6o, 5r) - Senior Software Engineer (31rj, 23o, 22r) - Product Lead (0rj, 1o, 1r…

This is a really interesting set of stats you have here. Heartening in the sense that rejection is a common and overwhelming likelihood and shouldn't be a source of dejection, but also kind of depressing in the sense that it's clear many, many companies (including some big ones) have a terrible hiring process.

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#149

Post by edblarney »

"Quite honestly given your questions [about vacation policy] and the fact that you are considering other options, [we] may not be the best choice for you."

You wouldn't want to work there.

" but the team has decided to keep looking for someone who might have more direct neural net experience."

Fair enough - but this has to be slim pickins. How many AI jobs are there out there? Realistically, very few.

Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs

#150

Post by dandermotj »

AstralStorm wrote: post #138
dandermotj wrote: post #77

Earlier quoted context omitted.

You're certainly not going to study Bayesian statistics without knowing (or at least having studied) what a p-value is.

Actually p-values are used way less often in Bayesian statistics than frequentist ones. The latter rely on statistical tests more. Bayesian stats tend to use likelihood ratios or Bayes factors instead of p-values for hypothesis testing. The trick in all cases is that you're comparing to expected results given some prior distribution. Most people use a dumb prior (e.g. Gaussian) and then they're confused when the numb…

I studied statistics - my point was that statistics is taught in a linear manner, starting with distributions and hypothesis testing (p-values) and then move onto more advanced treatments like Bayesian stats.
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