The Ultimate Guide to Land a Data Science Internship | schedule and time management survival guide

i hope that your to-do list for the day doesn't look like that but if i were to guess your next two to three months probably something similar huh if you're new here hi i'm tina and i'm a new data scientist at a fan company before we get started i just wanted to make a point if you're watching this video three months six months or even a year before you actually have to recruit that's absolutely amazing you see i personally didn't have that foresight in your case i highly encourage you to start learning sql because it's the most common skill that you see in data science interviews but do keep watching the video because i think the recruiting timeline and the schedule management tips are still really relevant so how do you manage your schedule while still being a full-time student don't worry here is my survival guide

number one fix your resume so the resume is by far the most important component of securing that first round interview because getting is the hardest part of the entire application process i suggest checking out the video that i'll be linking above where i go into more details about the best strategy for targeting your resume for specific roles as well as how to like pass ats and things like that

steps two and three are going to be in parallel step two is to apply for every single data science internship you can get your hands on and to do this asap this is especially important for people who don't have any relevant data science internships in the past for any data science experience and this is because data science internships are really hard to come by you want to maximize your chances of getting that first round interview by both casting your net wide and also applying as soon as possible step three is to figure out what you need to learn and also brush up on as you're going through the different roles and applying to them you start to notice that the core set of skills often include a lot of overlapping things for example sql is definitely going to be one of them and also probability and statistics and then there are also skills that show up once in a while for example product sense data sense and machine learning skills i suggest that you literally make a tally for the skills that show up the most and all the way down to the least frequent ones order this list from the most frequent to the least frequent skills as the order in which you learn things now repeat step two and step three until you start getting interviews

step four is to learn the stuff and to refresh your memory on anything that you might have forgotten as you get more interviews make sure that you're still applying to different positions but your focus should really be on learning right now research shows that multitasking actually really hurts performance so i try to always focus on doing one thing at a time and now is the time to learn in terms of the actual learning process itself i'm not going to go into too much detail here because i already did a video a while back which i'll link above where i learned sql from scratch in 11 days this is the learning approach that i use not only for sql but actually pretty much for anything so this also applies to our list of things to learn for the interview so yeah keep working down that list of skills going from most frequently appearing all the way down to the least frequently appearing my biggest tip here is to not be afraid to push back your interview by a week or even two weeks i find that most companies are pretty nice about it and they'll actually let you do that but in any case this is still a really short amount of time so you still want to prioritize ruthlessly and make sure you're learning the things that matter the most unfortunately you can't really have everything in life so there's probably going to be interviews are going to walk in and you know feel really nervous especially if you're super anxiety prone like myself and you're going to end up doing really poorly because they're going to ask you like some obscure question that you didn't have time to study because it's like really low priority on your list of skills to study and you know when you walk in even if you think that you're going to fail still try to do your best because you know who knows maybe you actually do pass through that interview or like even if you don't you can always chalk that up as extra experience in interviewing because interviewing itself is a skill

step five is to reevaluate so you know that you've reached step five when a you got a job congratulations or uh b you have gone through all the interviews and you applied for them and you interviewed and you didn't manage to get anything or c you apply to all these interviews these positions and nobody even got back to you so you didn't actually get the chance to do any interviews don't be too disappointed if you're in position b or even c because it's actually not that abnormal um like i said earlier these interviews for data science are really hard to come by and they're super competitive i guess like because data science is super cool these days and everybody wants to go for them but don't worry i have backup plans for you before i go into that though quick pause if you're getting value from this video please consider liking the video and even subscribing to the channel every like comment and subscription means so much to me and really motivates me to make more videos like these alright so what happens if those data science interviews just didn't work out well back up plan number one i have for you is apply for software engineering positions this is for people who have a computer science background or have some experience in software engineering or programming i don't suggest that you do this until you've exhausted all your data science options first though because software engineering interviews are an entirely new beast and it's really difficult studying for both software engineering and data science you might be wondering why i'm telling you to go for software engineering if you're for sure you're interested in data science well it's because you can actually sometimes interview as a software engineer and then ask for more data science related projects this is actually what i did for my internship at goldman sachs i interview for their summer technology analyst role which was a software engineering role and my interview was all legal questions and a little bit of behavioral questions and after i got in i actually asked the company if i could work on more data science related projects my team was super nice and they actually let me work completely on data science work and analyzing the data while the rest of the team worked in software engineering and data engineering you might be surprised i was able to do this but in reality software engineering data science and data engineering are actually really intermingled especially in the information age that we live in now data is literally everywhere so any reputable company that's doing software engineering in-house is definitely also doing data engineering and data science these roles get blurred a lot in reality so if you have a computer science background i highly suggest that you go for software engineering rules the best case scenario is that you go in as a software engineer and then you ask to work in data science projects and you can have a data science internship in the end and i mean the worst case scenario is that you have a software engineering internship which i don't think is that bad at all it's still really great experience all right so what happens if you did not land any data science internships and you don't have a computer science or programming background don't worry back up plan number two and in this case i can almost guarantee that you'll be able to get this as long as you put in the effort and that is a research position with a professor so this is not the sexiest internship that you can get but it does get your foot in the door and after your internship with the professor you'll be able to have relevant data science experience i'm not going to go into too much detail about this because i actually just released the video talking about research positions under professors so i will link that above as well sorry that this has been like a very lengthy heavy video um i it completely wasn't planned and i realized that a lot of the stuff that i talked about before really came together in this video so i really encourage you to check out the links um for my other videos to get more in-depth information

finally i want to give you guys some more general pieces of advice on how to manage your time and just like keep sane during this extremely hectic period of time which is recruiting season number one is to constantly reevaluate your approach to how to learn and also what it is that you're learning and this is because we really want to optimize for our ultimate goal in this case which is landing a data science internship i've mentioned this in my other videos as well but you know doing like learning lots of new things and doing different projects is super fun and really useful for learning but in this case we want to like you know really go towards that end goal number two is kind of related to number one um but it's being mindful about what courses you're taking and what extracurriculars that you're taking on and this is because recruiting season is really stressful and it also takes up a significant period of time so you want to make sure that you don't have a lot of other dedication so you can focus entirely where like you know as much as possible on recruiting number three is to not be too hard on yourself even if you prepare like super well and you know you're like perfect there's still a component of luck to this so my suggestion is just try your best and you know be okay with that i believe in you finally make sure to take care of your health both mentally and physically you know it doesn't matter what other stuff that you're doing but your health is the most important thing all right in summary step one is to fix your resume step two and three are in parallel and that is to apply to as many things as possible as quickly as possible and while you're doing these applications noting down what are the skills that occur most frequently step four is actually learning the skills and also refreshing your memory on skills that maybe you learn uh like two or three years back and they're going to be asking you about during these interviews step five is to reevaluate if you got a job congratulations and you can stop there but don't worry if you did it there's still two more backup plans the first one is to apply for software engineering positions if you have a computer science or programming background the second one is to go for a research position under a professor so you get that data science experience and you're good to go for the next recruiting season and that's it if you enjoyed this video i encourage you to check out my new series on how to land your first data science job and i'll see you guys in the next video