Hiring Process Of Data Scientist and Interns

Key Takeaways

my name is Krishna and welcome to my youtube channel today in this particular video we'll be discussing about the hiring process of a data scientist and in downes now before going ahead to this particular video guys if you are looking for Career Transition advice towards data science please make sure that you watch this particular video till the end I will be sharing some information some some very good YouTube channel so that you can actually refer that nowadays if you are looking towards the transition of data science the high end process you should basically know very very clearly like how the hiring process goes on for a fresher for some experience people are on two to five years five plus years you know and ten plus years for different different roles now if you know about data science they have various roles like you have you know data analyst data scientist interns you know then you have data scientist then you have senior data scientist lead data scientist principal data scientist and many more roles are there so we try to understand what are the various hiding crosses that usually happens so initially I will go ahead with interns so usually what what happens is that when you are in college in your final year and suppose you are looking for some placement opportunities or you want to go for some internship for some colleges right and when you apply in some colleges the first thing for an intern is that if you want to work in data science they'll give you a type of assignment and machine learning or deep learning and they'll basically give you around two days time and they'll tell you that you have to submit that particular assignment with respect to any machine learning use case for deep learning use case to them now once they once you do that particular level work within two days and then you submit them what they do is that they verify the things how you have written the code and once that is done they will actually approve it and they'll tell you that yes you can come for a face-to-face interview once then you will be having some technical discussion and then if you're good at that whatever work you have actually done in that particular project or the use case that the company has basically given if you have explained them properly with everything they'll definitely give you a chance for the internship now internships are usually for around two to three months or you know one to two months something like that right so after the internship what happens is that if the company likes your work they'll definitely hire you apart from that if you are in a final year and suppose you have just passed out of the college and is still looking for data science role this is also the same process in most of the companies they will they will actually give you an aptitude test suppose if you are in colleges they'll actually give you aptitude test you have to crack that aptitude test you know and then they'll move towards some technical round with respect to data science where they'll give you a use case to solve and you know they'll give you some amount of time then and there within that particular time if you are able to solve then they'll code then you go to the next round for the technical discussion and all now this is with respect to freshers and interns now with respect to some experience people like somewhere around one to five years of experience now guys whatever I am saying is based on my experience like how I have been also been taking many interviews for different different people in the field of data science I have also been interviewed in many companies so I will actually tell you in that particular way itself now if you are experienced guys like between one to five years so usually most of the companies they'll not be such an aptitude test at all but yes in some of the companies what they do is that they'll give you an assignment beforehand to solve something and they'll give you a one or two days time you know and then you have to submit that particular assignment to them now once you are able to do that once you're submitting the assignment if they like your you know implementation of that particular machine learning problem they'll call you for the technical ground now the technical ground usually in some of the companies that I have seen is basically two technical rounds in the first technical ground you know elite data scientist usually come or a senior data scientist usually come in order to you know ask your different different technical questions with respect to the kind of work that you do now and also give you the guidelines how you can crack the interview data science also guys now initially when they are asking you some questions make sure the first question will be that tell me about yourself right and at that time you'll be introducing yourself and you'll be telling that you have worked in this particular thing in other what all kind of work you have done in machine learning deep learning how you have done what are the challenges that you have faced make sure that when you are telling this right try to tell him try to tell the interviewer the things that you are very very good at you know like you are very good at thing and anybody if they ask you this particular question you'll be able to answer that so you have to go in some flow and if you are able to go in that particular flow definitely the interval will be more keen to ask you questions on with respect to that particular topic and once you hear that particular topic and automatically you will also be feeling confident because you have already worked on to that right so this is how it goes so once you go through this particular technique till the end and you tell him the things right and again I am telling you the one of the very good quality to become a data scientist is that you need to be a good storyteller so when you are telling about your project you have to tell in such a way that you are actually explaining him from end to end you know and by that the interview will also get the context about the work that you have actually done so this is very very much important guys you have to be a good storyteller you have to tell in that particular pattern so that he understands and suppose if there are some questions that you don't know you know there I not say that you have to know everything and machine learning and deep learning you don't know it says it is fine you tell them that you tell him that you have never worked on that so definitely he'll also consider that particular point also so make sure that you be a good storyteller tell all the things that you have actually worked on you are very good at you know prepare your talking skills in that particular way it would be definitely helpful now once you are able to clear your first technical ground there will be the second technical round where a senior manager you know the project manager or usually the director comes and talks to you he understands like what you are actually interested in if you are able to create I mean clear the first technical round and apart from that the implementation that they had given in the first time so I think the second round will be easily be able to clear it because then the talk will be with respect to the project what kind of work you will be doing the the technical manager or the director will be actually explaining about it and definitely if you are able to do this you will be able to clear the interviews now for the people who are above five plus years because four above five plus years they go to some senior data scientist position early data scientist project position and when I talk about more than eight years it years of experience you usually go as a lead data scientist of principle data scientists now in this there will probably be three technical interview rounds okay there will not be anything like they'll then they'll not give you a problem statement then tell you to solve them in there but instead they'll focus on what are the different different projects that you are implemented they'll try to drill with respect to each and every concept that is basically presented in your resume in write about NLP suppose if you have written about machine learning in machine learning have used this algorithm you used auto ml you have used h2o dot AI you have used deep learning techniques where you have used for faster our CNN so all these particular techniques if you have written in your resume they'll try to deep dive into each and every topic the interviewer will be pretty much interested to understand what work you have actually done how you have actually you know improve the business what profit you have actually made what are the things that you have actually automated in your company and many more things right and that depends on the type of projects that you are basically doing now this particular round is very very important when I say three technical grounds because the first round will basically be taken by a read data scientist the second round will be going with respect to a principal data scientist and the third run will be with respect to the higher management and again guys there will be one final HR round that that nobody can stop because that round is final round over there but I'm just concerned about the three technical part you know once you're able to clear the interview in a technical interview then definitely that chart will be the last round over there so in the first round what will happen is that they try to understand about your project what kind of work you have done they'll ask you most of the technical questions about machine learning algorithms about deep learning algorithms what are the challenges that you have faced how we have basically implemented it what is the team size that you have basically managed how many people who are there in your team and all this different kind of questions now once you clear this and probably a lead data science should be taking care of that if you go to the next technical round this technical round for this I mean for the people who are more than five plus years it will be little bit difficult because the principal data scientists will be taking up and he'll be trying to understand with respect to the complete project overview you know from the data collection stage how you have actually data he may also ask you some of the big data concept because that is also very very much important and if you are applying for a role of lead data scientist or principal data scientist or a senior data scientist you need to have some amount of knowledge for that so he will be trying to understand or drill down all the modules of the lifecycle of a data science project in each and every part what are the challenges that you faced and this this second round will be the most of his strong what I feel for five plus years of experience because there the principal data scientist will be drilling you down completely you know he will try to understand it because for the position that you are going it is a very responsible position you know there will be people who will be under you you have to also help them so you should be a much having that capability to do handle so many people at a particular project and again there are a lot of technical questions that come up with respect to a project whenever you are working on you should also be able to answer that for your juniors at all yes then after that once you clear that particular round you go to the director ground direct well again me explaining you they'll just ask you okay what are your any questions that you basically have with respect to the projects so you will probably ask that what are the kind of work that you look then he'll completely explain you like what are the things that he will basically be giving you what are the activities that you'll be doing and definitely after that particular talk I think the next last round is basically that Charles now guys uh again I just told a hiring process of a data scientist but there are some very very key important points that you have to put in your resume and now with respect to data science there are some very very important topics that you have to always mention you have to always mention in your resume so first change with respect to the machine learning right in machine learning try to make sure that you put different different algorithms not simple algorithms and you also try to put all the hyper parameter you know hyper parameter tuning techniques you like using Ritzer cv randomizer cv auto ml because that is also a very important part in any any data science project okay now while you have put that you know when you have put that also make sure that you put some amount of information regarding language processing about principle component analysis all the different techniques of dimensionality reduction all this particular stuff has to be put and I know many people have learned that try to apply that in your project whenever you can it will also be very very helpful for you and the other thing that you can also put in your resume is related to the database information if you have worked on Hadoop yeah if you have some basic knowledge about that just an overview about databases and for experienced people I think you need to put some abundant amount of information regarding databases the whole pipeline of data science lifecycle and make sure that guys you you whatever you're writing in a resume is the truth thing otherwise if you are not able to answer that definitely that will put our negative Express impression about you so now if you are looking towards the transition towards data science and you also want to are working in different different lighting companies and solving different different projects this is a very good channel called a springboard India please go and look at that particular channel the link is basically given in the description so yes this was all about this particular video I hope you like this particular video please do subscribe the channel if you are not already subscribe I see you all in the next video have a great day ahead thank you one and all