Clicked hoping he was going to do data science on his failed interview data
Some Reflections on Being Turned Down for a Lot of Data Science Jobs
121–130 of 175 posts
Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#122At least you have been told the reasons, even if they are true or not. I recently had many tech/behavioral interview with team and passed, but after a review with VP of X, saying we decided not to move forward is way worse than this. I still keeep wondering 'What is wrong with me?' even after years of interviews. I have some suspicions, but never a promising answer. If I oneday found a company, first company policy w…
Even just a little 'context' can help. I had a candidate ask me after the last position I held interviews for "Can you tell me what to improve? I was honestly surprised I didn't get the position, given how well our interviews went".
And he was right, too.
But I broke it down as follows. We received 300+ applications, we filtered down to 100 that were worth even reading in detail. From those we took 50 that we discussed/scored as a group, and came up with 15 people we wanted to interview. Of those we interviewed 10, and of those we interviewed 5 a second time, and 3 a (brief) third time.
"So yes, you did well, and we'd like to keep your name and reach out" (said sincerely). But for him knowing that he didn't screw something up, there was just an even better candidate and he was realistically still in the top 1-2% of applicants was confidence-boosting.
Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#123My analytical thought process on DS interviews: - Signal is still quite low among noise, even with long multiple interviews, take-home homework, coding challenges, etc. Most relevant data is still hidden and takes months-years to come out. - Companies seek to minimize false-positives much more than minimizing true-negatives. - It's a numbers game from both ends because the probabilities are low, due to above 2 points…
Woe betide the company that asks for a take home project, especially one that isn't just 50 lines of an algorithm (I'm talking one that I recall that asked for parsing Apache logs from a stream, displaying moving averages for URLs, aggregates, having high water mark "alerts" and resetting when rolling averages dropped below that, some unit tests and docs...
And doesn't bother to respond after you submit. I'm certainly not the world's best coder, but my solution met all those requirements in a reasonably elegant manner, and took several hours (10-20?) to make comprehensive.
That gets you on my shit list, and people I know get to hear about it, too.
Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#124I manage a data science team and revamped the hiring process pretty substantially about a year ago, to good results. Nothing in here is particularly original, but here's what we do: 1. Break down "data science" into several different roles–in our case, Analyst (business-oriented), Scientist (stats-heavy), Engineer (software-heavy). Turns out that what we mostly want are Engineers-Analysts, so our process screens heav…
I've been looking for a job, and I've found how vaguely organizations define their data scientist and analyst roles in their job postings really frustrating. They tend to have a short description of the role, which is generally filled with buzzwords, followed by a list of requirements. I wish organizations would talk about what they wanted to do with their data instead. For instance, a common description might say th…
> I wish organizations would talk about what they wanted to do with their data instead.
It may seem like a daft question, but have you tried asking them? They may clam up and refuse to give you anything, but I would imagine most small companies would be willing to talk about what the role involves. It's a bit late at the end of the interview to be asking "So what would I be doing?".
You may find out that they're working on some data which is e.g. image-heavy and you happen to be an image processing expert.
Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#125Earlier quoted context omitted.
> first company policy would be to tell the candidates to tell why they were not hired in a polite way. And your lawyers would strongly advocate against that. In most cases they can't/won't tell you because it could open up legal liability. If they say a reason for you, but then hire someone else to whom that reason also applies and you find out, you could sue them. Or you could find a way to twist it into something…
This is part of why I dislike employment anti-discrimination laws. They probably worked better for manual labor jobs. Of course, there is also firing where the laws vary by state. I think CA is one of the most strict, right?
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Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#126Earlier quoted context omitted.
I've probably interviewed about 70-100 such people in the past year and a half. Exactly 1 such person was qualified (I hired him). The issue in my view is the following: people who know both statistics and computer science are extremely rare. People who actually understand statistics are rare. I can probably weed out 1/3 to 1/2 of candidates simply by asking what a p-value is, or what precision/recall are (this inclu…
Ignoring what a p-value is does not mean that you don't know statistics. p-tests are not some inherent statistical property, they're just a useful model for significance. People coming from a CS background most likely didn't have to deal with p-values, but they can still be good at linear algebra or bayesian statistics. (not sure I can defend somebody that does not know what precision/recall are)
I can't imagine how you could learn Bayesian stats w/o starting with a basic inference class, which will cover p-values at length.
Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#127> you rarely truly know why you were turned down. Bit of a silly article. You could say this about anything. And I don't see what the problem is with never being contacted, if someone doesn't want me for whatever reason, I don't really want to hear from them again.
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Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#128That sucks.
That said, what is this?
a) "I cannot do X" b) "But here is some advice on how to do X"
I mean... why would anyone listen to the advice that is proven to lead to failure? Serious question.
Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#129I manage a data science team and revamped the hiring process pretty substantially about a year ago, to good results. Nothing in here is particularly original, but here's what we do: 1. Break down "data science" into several different roles–in our case, Analyst (business-oriented), Scientist (stats-heavy), Engineer (software-heavy). Turns out that what we mostly want are Engineers-Analysts, so our process screens heav…
I've been looking for a job, and I've found how vaguely organizations define their data scientist and analyst roles in their job postings really frustrating. They tend to have a short description of the role, which is generally filled with buzzwords, followed by a list of requirements. I wish organizations would talk about what they wanted to do with their data instead. For instance, a common description might say th…
>>I've been looking for a job, and I've found how vaguely organizations define their data scientist and analyst roles in their job postings really frustrating.
I lead a Data Science team and part of the struggle with writing sensible job descriptions is that there are too many people providing input into the job description. HR can also put their hand in the pot when they try to use buzzwords (e.g. Hadooop) to internally justify why a role with 2 years of experience needs to be paid like other roles (e.g. traditional Excel based Analyst) with 5-10 years of experience.
>>They tend to have a short description of the role, which is generally filled with buzzwords, followed by a list of requirements. I wish organizations would talk about what they wanted to do with their data instead.
One major challenge for Data Scientists is how hyped the role is, leading to people in an organization believing whatever they want about Data Scientists. Are you a leader who wants a business analyst who can use software and interface with IT? Data Scientist. Are you an engineering manager who wants a person who can interface with the business and use machine learning? Data Scientist. Are you a VP who thinks big data and ML is the problem to your bad or non-existent data? Data Scientist. Do you want somebody who can exhale the maximum amount of hot air while still sounding like a tech and math genius? Data Scientist.
Also add in that business people with minimal experience in modern Analytics are trying to build up Data Science and Analytics capabilities in their own part of the organization because they realize Excel is not the answer to every question. I've spent a lot of time speaking with people to help them understand the type of people they need to hire. Sometimes people are sensible and sensible job descriptions and expectations come from that. Other times they are adamant about what they need (even if they are wrong) and the end result are convoluted job descriptions that are either never filled or filled with the wrong person.
Re: Some Reflections on Being Turned Down for a Lot of Data Science Jobs
#130I looked at this resume. it looks good but his job history is a major concern. Of course, some might say why even invite him to an interview, perhaps they gave him a chance only to discover in the interview process that he's really impatient and not willing to stick around for long?
There is a ramp up time for new hire, which could be a couple of months. So durations of a year or less doesn't look good. I personally like to see minimum of 2 years for each job. Of course, too long can be a concern too unless they really grew in their role.
I agree with his conclusion, Network is king, but I also believe in listening to the universe. If everyone is "wrong", maybe you are the problem. If lots of people don't wish to hire you after you have solid experience in the industry, something is wrong with you and you are being stubborn by refusing to recognize it and fix it.