Some Reflections on Being Turned Down for a Lot of Data Science Jobs • Hacker News Board

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

#171

Post by mattfrommars » Thu, Mar 09, 2017, 6:36 AM UTC

Ok, this is a little worrying. I've read through the all the conversation here but is it really that difficult to get jobs for people who already are involved in Data Science? Here I was thinking if I do a course on Data Science fundamentals of computer science online, I would on tract of getting a computer science/data science job.

My future really rests upon this. I have a degree in mechanical engineering with irrelevant experience. My only regret is not doing bachelors in computer science.

I wouldn't lie if all the post got me little tensed and made me thinking, "what am I doing with my time". About to finish introduction to Computer Science using Python on Edx.

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

#172

Post by kafkaesq » Thu, Mar 09, 2017, 11:42 PM UTC

kafkaesq wrote: post #159

mulmen wrote: post #135

Earlier quoted context omitted.

I recently asked about the "unlimited vacation" policy and received a vague answer about "establishing expectations with your manager" and then was told they went with someone else. I thought about if I should ask or not but I honestly don't understand how such a policy could be good for employees so I wanted an idea of the culture that allows it. If that question contributed to them not giving me an offer then good…

No need to keep asking. If your get is telling you that something's not quite with this "unlimited vacation" policy -- it's because it's a sham, basically. And everyone at the company knows it -- including and most especially, upper management. Because that's after all where it originated.

EDIT: 'get' should have been 'gut'.

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

#173

Post by lifeonahilltop » Fri, Mar 10, 2017, 2:27 PM UTC

SatvikBeri wrote: post #35

I 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…

Can I ask what are the rough percentages of the three types of data science jobs in the industry? And is there an easy way to search for only one type of jobs (such as using some particular keywords on indeed.com)? I have some advantage only in the scientist/stats-heavy type of data science jobs and would like to better focus my job-searching effort. Thanks.

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

#174

Post by halflings » Tue, Mar 14, 2017, 2:18 PM UTC

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.

That's OK. The article was talking about somebody interviewing for a search-related position (where precision and recall are usually what you are optimizing for). I guess they might be called differently in econometrics?

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

#175

Post by halflings » Tue, Mar 14, 2017, 2:21 PM UTC

x0x0 wrote: post #126

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)

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.

I did Bayesian stats without ever discussing p-values. Not al classes discuss them. (my background is ML, where p-values are not as useful as say in biology or any field relying on experiments with control groups)