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

tdhopper.com

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

#161

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.

Reading this thread makes me want to cry. The world is filled with morons.

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

#162

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.

Yes, for example some take months with everyone loving you the entire way, for a single person to interview you and reject you without a reason.

I'm glad I had those interviews early on, so now when I see an interview start to drag on, I cut it short as it doesn't look like a priority on their end.

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

#163
post #129

Earlier quoted context omitted.

>>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 intern…

how do you choose candidates for an interview? I can't even get a call back for an interview lined up. I have done NLP, got a masters degree in computer science from Penn, plenty of experience with big data such as hdfs and hive, spend my free time doing what ever data science I can. but obviously doing something wrong. any suggestions? Here is my linkedin account: https://www.linkedin.com/in/karl-dailey-02557b65

May I offer a couple of quick suggestions? I've never hired for Data Scientist positions, but I've hired for plenty of other ones.

1) Change your profile picture to something serious. Get a collared shirt and a nice background outdoors. No tie. People will unconsciously judge you on your picture, so you want something that shows you're a professional, but you're confident and happy in life.

2) Think hard about your job titles. Your latest job is far more than just a "Data Analyst". It seems closer to a Scientist or Engineer role, even if your company doesn't call it that. "Analyst" makes people think of entry-level positions. Your DBA-Programmer position is more like a Software Engineer/DBA/System Admin position. If you can't pick one, generally those all-in-one positions can be known as Systems Engineers. Whatever you do, make sure that DBA isn't the primary thing people see. In general, sell your previous positions more. Like "IT". That's not a title, that's a department.

3) Expand on your projects section more.

4) Make sure your resume matches your LinkedIn. People absolutely look you up on there. I did it all the time. When the two didn't match, I was suspicious.

Good luck.

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

#164
post #154

Earlier quoted context omitted.

Functional programming for a lot of numerical computing maps easier to mathematical notation. However, Scala is usually a worse choice than Java for numerical computing since everything is a boxed type.

This is straight up false, why do you think Scala doesn't have primitive values? Long will be either a value or reference type as needed, despite being spelled only one way instead of two different ways in java.

A 'primitive type' is one which can be directly operated on by intrinsic CPU instructions. My understanding of Scala was that all objects (such as Long, Int...) are encapsulated inside of an object.

Therefore an array of boxed types will not be memory aligned; and any vector instructions (which are very important to scientific computing) cannot be used.

Perhaps something has changed in Scala land since I last looked(??).

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

#165
post #154

Earlier quoted context omitted.

This is straight up false, why do you think Scala doesn't have primitive values? Long will be either a value or reference type as needed, despite being spelled only one way instead of two different ways in java.

A 'primitive type' is one which can be directly operated on by intrinsic CPU instructions. My understanding of Scala was that all objects (such as Long, Int...) are encapsulated inside of an object. Therefore an array of boxed types will not be memory aligned; and any vector instructions (which are very important to scientific computing) cannot be used. Perhaps something has changed in Scala land since I last looked(…

No, it has been worked the way GP wrote since approximately forever.

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

#166

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…

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

Sure, but that doesn't sound unreasonable.

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

#167
post #129

Earlier quoted context omitted.

>>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 intern…

how do you choose candidates for an interview? I can't even get a call back for an interview lined up. I have done NLP, got a masters degree in computer science from Penn, plenty of experience with big data such as hdfs and hive, spend my free time doing what ever data science I can. but obviously doing something wrong. any suggestions? Here is my linkedin account: https://www.linkedin.com/in/karl-dailey-02557b65

I've got some feedback and you might see it as mean and brutal. But what I'm doing is being honest as how I would evaluate a resume that looked like your LinkedIn profile. I'm just telling you what I'm thinking.

The first thing I did was look at your current position and I immediately became skeptical. You have been at your position for 10 months, yet you have done a lot of fancy sounding things that seem to have no connection to each other. To me this is a huge red flag that you're just grabbing some data, churning through some code you found on StackOverflow or in a book/documentation, and then making grand claims about the work you are doing at ComCast.

Your use of buzzwords only makes me think this more.

For example "Churn forecasting: probabilistic modeling of deletion rates on dVR with a beta binomial distribution to forecast the number of devices that carried a show over 300 days. Maximum Likelihood Estimation was used to derive distribution parameters."

This honestly looks like you saw a tutorial about an R-library and then you copy/pasted the documentation for one of the functions into your profile. By using so many buzzwords (including the term deletion rates), you've left me wondering if this is something you actually did or just something you made up. If you actually defined and derived the Likelihood function you should state that. Otherwise saying you used MLE means nothing since many functions in R use MLE under the hood.

Another one is "Built node.js/angularjs integrated tool to allow analysis team to test the sensitivity of KNIME workflows for forecasting." In my mind I'm thinking, what exactly does web programming have to do with KNIME? What exactly do you mean by sensitivity? How are KNIME workflows sensitive? Do you mean you are checking the accuracy of forecasting models built in KNIME? Lots of Data Scientists will have no idea what node.js and angular are and many will not care when they find out. Data Scientists may build charts using JS, but very few will be building Web based UIs themselves (I assume this is what you are trying to say?)

To be honest, I have no idea what you do in your job. Are you actually a Data Scientist as part of your job duties or did you develop an interest in Data Science and you have access to Comcast data so you've been playing around on your own?

At a hiring manager, I want to know the person I'm evaluating has spend time working on a business problem from start to finish. This means they thought about the problem, defined how to answer it (or figured out how the business owners want them to define it), figured out which data was relevant, thought through a model if it's a business problem that can be addressed by a statistical or ML method - this includes thinking through how the output of model will be used by the larger business - and making a lot of mistakes and changes in this journey.

If the person is just getting into Data Science, I want to know the person has the analytical and metacognition skills to think through a business problem. If they have that then I evaluate their thinking with models.

I'd recommend you trim down your LinkedIn profile and focus on the projects which took you some time (e.g. a month or longer) and where you had to iterate a solution. Use these projects to illustrate what you actually do at your job.

It's possible that you've done everything you state. You may be working with a team of people. At a large company you'll have other teams supporting you with data collection, cleaning, and putting the data into a shape that makes it amenable to machine learning and joining with other relevant sources. If that's the case, focus on projects where you were leading the project in some way and emphasize how you worked with and led the team.

But based on your LinkedIn profile I'm skeptical and a resume like this would not pass my filter. The HR person I work with would see your profile as impenetrable. If they can't figure out what you do and what you have done they are not going to send your resume to me.

Finally, can you move into a role at Comcast that gives you an official "Data Scientist" title? From what I've heard Comcast has a solid Data Science practice and it seems like they have some really interesting data. Finding that combination is really hard. Many good or potential Data Scientists end up at jobs where they are unhappy because the Data Science culture and/or data is awful.

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

#168

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…

> Software QA Engineer background + no CS degree implies I have no technical skill. Sure, but that doesn't sound unreasonable.

>:|

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

#169

The too many jobs knock I can understand...I'm just plain old Midwest developer guy, so maybe I don't understand the nuances of a market like Silicon Valley or the like that is inundated with software jobs. Still, when I read HN I often get the impression that there is more focus on getting that next great offer than actually doing a given job...so much so that the ability to be perceived as valuable at interview/scr…

You may well be right.

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

#170

Earlier quoted context omitted.

Why do you think candidates for data science jobs aren't qualified relative to other positions?

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…

When you say "know statistics", how high are you placing the bar? Lots of people are forced to take one stats class (for non-specialists) in college, and it goes up from there.
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