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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

#41

Post by dwpdwpdwpdwpdwp »

ska wrote: post #27
dwpdwpdwpdwpdwp wrote: post #20

Earlier quoted context omitted.

I'm surprised people bother spending so much energy looking for someone who is both a statistician and a computer scientist knowing they are so rare. There are so many more statisticians who can at least communicate and work effectively with developers and vice versa. Why not just compose a team? I feel like just like other professionals have assistants, statisticians should have them too, and they'd be focused on th…

This is a classic problem that shows up equally with lots of related areas: numerical work, statistics, ML, signal processing etc. "just compose a team" sounds easy, doesn't it? Unfortunately there are lots of failure modes involving different parts of the team not really understanding what each other are trying to do, let alone what they are doing, and subtle errors getting by people who don't know what to look for.…

As an engineer, I usually know better than to use the phrase I hate to hear: "why don't you just..."

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

#42

Post by kevinburke »

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…

> Internal recruiters have hinted that my Software QA Engineer background + no CS degree implies I have no technical skill.

They're really trying to mitigate risk that they pass you along to engineers and the engineers say "why am I looking at this person with no formal qualifications" and then the recruiter feels like they've wasted the time of the engineering team. It's stupid but insidious.

If you can I would suggest trying to bypass the recruiters and contact the engineers/hiring manager directly; ask them out for coffee and ask for advice on starting a career in data science, or show them your portfolio via email there.

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

#43

Post by kenjackson »

Bootvis wrote: post #34
halflings wrote: post #12

Earlier quoted context omitted.

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)

Regarding precision/recall, I've a background in financial econometrics and this is the first time I encounter the terms.

I think the problem is that certain subfields use different terminology to mean similar or identical concepts. For example, while I'm in software, I tend to hear the terms sensitivity and specificity. They are historically medical terms. They aren't identical to recall/precision, but I think you can derive one set from the other.

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

#44

Post by minimaxir »

EternalData wrote: post #23
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've seen your posts on Spark. That's sad to hear. Are you applying online or via getting coffees with people in the data science team and just talking shop? The latter seems to have a high conversion rate if you can nail it.

Mostly online; I've been too busy to network during the weekdays unfortunately, which is something I'm working to fix.

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

#45

Post by tom_b »

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 wonder if you are less impacted by the lack of CS degree than by your "Software QA Engineer" label.

My own experience was that my initial position as a software performance engineer resulted in a perception that I was a "tester" without technical skills despite having multiple CS credentials and published code in practitioner-oriented sources.

Overcoming recruiter biases was such a struggle that I now routinely counsel students and early career programmers to carefully consider whether job role perceptions would negatively affect their future prospects. I also tell them, when financially viable, to not take on roles where hiring orgs cannot give them a day-to-day job description that directly matches their desired career path.

This advice seems quite challenging or maybe misguided for data science careers though. It seems like just getting an entry-level data science job might require a dedicated MS in either CS or stats, with a healthy set of projects in whichever of those two subjects you didn't spend grad school working on to prove yourself . . .

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

#46

Post by Bootvis »

kenjackson wrote: post #43
Bootvis wrote: post #34

Earlier quoted context omitted.

Regarding precision/recall, I've a background in financial econometrics and this is the first time I encounter the terms.

I think the problem is that certain subfields use different terminology to mean similar or identical concepts. For example, while I'm in software, I tend to hear the terms sensitivity and specificity. They are historically medical terms. They aren't identical to recall/precision, but I think you can derive one set from the other.

That certainly seems likely and a good thing to keep in mind when you're giving or taking an interview!

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

#47

Post by kafkaesq »

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 that they pretty much don't really want to be there in the first place), make them answer some made-up questions (which may or may not be coherently presented; or even particularly relevant to the job description) -- combined with the background stress of being unemployed, and/or stuck in job they absolutely HATE, and can barely stand another day of -- and see how they do."

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.

Great -- so they're basically accusing you of being a slacker (not really into the work, only interested in what's in it for you, etc). Which is quite a presumptuous attitude to take in response to a perfectly reasonable question about the value proposition they're asking you to consider (a question for which it might be in better form to wait until the later stags of the negotiation process to bring up... but that's a very minor style point that you definitely shouldn't be dinged for).

"Quite honestly" that attitude sucks. And you don't need to feel bad about being "rejected" by people like that.

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

#48

Post by _flbt »

I was coming from academia with no real competitive background in machine learning/predictive analytics/statistics when I started applying for data science positions. I was coming from a post doc in computational neuroscience, and had done ML/your run-of-the-academic-mill stats as part of my thesis, but never had formal training in it. I landed a lot of interviews (and applied for an ENORMOUS amount of positions), but it took me a while to land a really solid offer. So just keep at it.

Once I got that offer and 'data scientist' was listed as a position on my resume, I've had at least one or two recruiters reach out to me each week. Not just your 'bulk tech recruiter', but individual hiring managers/team leads from companies who had no interest in me prior to the title change.

Hell, I had a manager I had already interviewed with from another company (and got rejected) reach out to me TWICE to come back in. To be honest, I'm not entirely sure he remembered that I had interviewed there only a month earlier.

All after I had the title change on my resume. What I'm getting at, is for me, the title change really opened up doors. I figure 'data science' is such a huge buzzword now, recruiters look more for that buzz word than they do for the actual content of what you've done on your resume. I'm sure it will die down at some point.

This may be more prominent outside of silicon valley where I am, and (in my opinion without any facts to back it up), where I feel more weight is given for the title than the substance.

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

#49

Post by yttrium »

tom_b wrote: post #45
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 wonder if you are less impacted by the lack of CS degree than by your "Software QA Engineer" label. My own experience was that my initial position as a software performance engineer resulted in a perception that I was a "tester" without technical skills despite having multiple CS credentials and published code in practitioner-oriented sources. Overcoming recruiter biases was such a struggle that I now routinely cou…

I had a similar experience. My first job out of college was for a Developer Role (building testing frameworks, maintaining and building browser extensions) but the job was titled 'QA Developer' so I had a hell of a time the first time I tried to find a new job. Never mind that I wrote thousands and thousands of lines of application code, lots of recruiters would deny me on the basis that my background didn't fit.

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

#50

Post by melvinmt »

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…

> my Software QA Engineer background + no CS degree implies I have no technical skill

It's OK to leave stuff out on your resume if it's not relevant (and maybe even harmful) to the position you're applying for.

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