Data Science Interview Study Guide
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Data Science Interview Study Guide
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Re: Data Science Interview Study Guide
#2It bothers me that so many of these guides are aimed at passing the job interview instead of teaching the topic at hand.
- I want to be excited about the possibility of becoming better at the topic, not fantasize about crushing an interview
- If there is a major difference between the skills needed for an interview and the actual job (as the concept of interview perparation suggests), that's bad in all kinds of ways
- The interview prep articles often present the material in an unattractive way, as a list of requirements that need to be fulfilled, without an explanation of how it all fits together.
How about leading the student along, from a small sample project, showing the pitfalls of not understanding statistics properly, to a larger project where the data is put into a database, motivating the study of SQL, to doing some programming related to the toy problem at hand, motivating a deeper dive into programming fundamentals? How about inspiring the student about the beauty of the topic, about the possibilities and powers they get with each new little skill that they acquire?
Re: Data Science Interview Study Guide
#3It bothers me that so many of these guides are aimed at passing the job interview instead of teaching the topic at hand. - I want to be excited about the possibility of becoming better at the topic, not fantasize about crushing an interview - If there is a major difference between the skills needed for an interview and the actual job (as the concept of interview perparation suggests), that's bad in all kinds of ways…
> If there is a major difference between the skills needed for an interview and the actual job...
The problem is that the exact skills required for a job cannot be measured within the timespan of an interview, so instead closely related skills are measured. Until somebody solves this problem interview preparation makes a lot of sense.
Re: Data Science Interview Study Guide
#4It bothers me that so many of these guides are aimed at passing the job interview instead of teaching the topic at hand. - I want to be excited about the possibility of becoming better at the topic, not fantasize about crushing an interview - If there is a major difference between the skills needed for an interview and the actual job (as the concept of interview perparation suggests), that's bad in all kinds of ways…
> It bothers me that so many of these guides are aimed at passing the job interview instead of teaching the topic at hand.
This is another manifestation of the "Goodhart's Law"
Re: Data Science Interview Study Guide
#5It bothers me that so many of these guides are aimed at passing the job interview instead of teaching the topic at hand. - I want to be excited about the possibility of becoming better at the topic, not fantasize about crushing an interview - If there is a major difference between the skills needed for an interview and the actual job (as the concept of interview perparation suggests), that's bad in all kinds of ways…
You have a point, but I think there is more to it.
I have failed twice the last year to be offered a DS position after going through all the interviews, references and HR personality tests. I would say that ~50% of the issue was me (0 not nailing every question) and the other 50% was the employer not understanding how to screen for the right people (= them lacking answers to questions they didn't ask).
I think there are two distinct skills: the skills you need for the job, and the skills you need to get the job. Maybe these guides cater to latter.
Re: Data Science Interview Study Guide
#6It bothers me that so many of these guides are aimed at passing the job interview instead of teaching the topic at hand. - I want to be excited about the possibility of becoming better at the topic, not fantasize about crushing an interview - If there is a major difference between the skills needed for an interview and the actual job (as the concept of interview perparation suggests), that's bad in all kinds of ways…
Welcome to the wonderful world of interviewing in tech! And people wonder why most software is shit.
Re: Data Science Interview Study Guide
#7It bothers me that so many of these guides are aimed at passing the job interview instead of teaching the topic at hand. - I want to be excited about the possibility of becoming better at the topic, not fantasize about crushing an interview - If there is a major difference between the skills needed for an interview and the actual job (as the concept of interview perparation suggests), that's bad in all kinds of ways…
> If there is a major difference between the skills needed for an interview and the actual job... The problem is that the exact skills required for a job cannot be measured within the timespan of an interview, so instead closely related skills are measured. Until somebody solves this problem interview preparation makes a lot of sense.
I think evaluating the skills is not difficult within the timespan of an interview, if done right.
Let's sit down at a specific problem I am working on. Let me tell you what I'm doing with the tools that I have. Your past work was in some way similar, and you can relate to what I'm doing in some way. Either you can jump right in and take over the keyboard, or you can tell me how you solved a similar problem with your tools and frameworks. I can show you how it's done with my setup, and teach you a few things in the process - which you will easily pick up as you have related experience. You got either questions that are exciting, maybe challenging me how I am doing it, or maybe teach me just a keyboard shortcut I didn't know, proving the time and effort you spent on this. We are both excited to learn a lot in a short amount of time and I know I want you to work with us...
Re: Data Science Interview Study Guide
#8At Kyso (https://kyso.io) we see a lot of people get hired into data-science jobs and the biggest success factor that I've personally seen is having some example's of projects that the candidate has worked on. This can be either public projects online (thats what we started Kyso to help with!) or a description of a project they worked on while studying/working.
Something I've noticed about data-science candidates is that they are very happy to jump into the technical details of an implemented model - but sometimes struggle on is communicating the reasons for the model in the first place and how it can help the company/research project. A lot of data-science projects are smaller ad-hoc jobs where the data scientist is trying to answer some business question and here communication is a vital skill.
Re: Data Science Interview Study Guide
#9It bothers me that so many of these guides are aimed at passing the job interview instead of teaching the topic at hand. - I want to be excited about the possibility of becoming better at the topic, not fantasize about crushing an interview - If there is a major difference between the skills needed for an interview and the actual job (as the concept of interview perparation suggests), that's bad in all kinds of ways…
That's because these guides are specifically designed to help someone pass an interview. What you're describing is the experience that one would get from taking an online data science course.
Re: Data Science Interview Study Guide
#10“Statistics is a broad concept so don’t get too bogged down in the details of each of these videos. Instead, just make sure you can explain each of these concepts at the surface level.”
Lol, well now, there’s a recipe for success right there.