How to Land a Data Science Job Without Experience (My New Grad Story!)

this means doing something like marketing yourself almost as you are like the product hi guys it's Jay here I am back without glasses because the reflection was really distracting to me when I looked at the videos afterwards besides that fact I wanted to do a video on how to get a job in data science without any experience and without like a masters or a PhD mostly just kind of giving advice about my experience trying to find a job in that similar format and I think there's a lot of videos like this out there but I really want to just talk more about the story of how that came to be how I started from looking for a job in data science and a career fair my senior year and then one year later became the first data scientist on a team of 10 people with four engineers and I was one of them basically doing all the data engineering and data science work and so how did I get to that point right and then how did I actually do data science when when was acted such a small venture-backed startup and so yeah let's start from the very beginning so why is it so hard to get a job in data science right and this kind of comes from what I didn't know about the field when Iowa is actually a new grad in that the fact that when I was at this career fair right this is the first time I was looking for like a data science job I had just come off an internship at Cisco where I worked as an IT engineer intern which isn't like an IT intern specifically but just like an engineering intern within the internal divisions org I could say it any kind of way I want but I won't make it sound better but I definitely like try to change it to sound better right and I'd change into more of like an analytics internship job so that's kind of the first thing that I did to try to make myself a little bit more polished for searching for new grad data science jobs right but as I was that that career fair I'm looking around there honestly wasn't that many data science jobs out there right for new grads and you know they'd have like these job postings and I talk to the recruiter or I talked to engineer and at the career fair and they basically say oh yeah the are reserved for generally people with a little bit more experience or like our masters or PhD students that are coming here but we'd love to consider you for you know some other role in the future or they push me to engineering but then engineering would wouldn't see enough experience on my resume and I wasn't a computer science graduate right and so mm-hmm how exactly was it possible to like get a data science job at that point and I was mainly like losing a lot of hope until I came across one booth at this career fair where I talked to this engineer that initially sounded really excited he's like okay I'll send it over to my friend he'll take a look at it and then the friend comes like amazingly from like behind the booth he comes out takes a look at my resume and basically just throws it in the trash right in front of me and goes you don't have what it takes you know you're not qualified data scientists all need PhDs at this point and I was fuming right like because I'm a just young like hothead post teen I don't know just college graduate and senior and I just generally couldn't imagine how this guy could be so disrespectful and so flippant about what I wanted to do in terms of a career like I just heard of data science and I thought it'd be really interesting and so I was arguing with him and then he brought up this metaphor with a pilot and so you're saying like and I was saying okay like don't you think that if there's gonna be a lot more openings for data science in the future that there should definitely be lower requirements instead of just having PhDs come in and become data scientists and he says okay yeah that might be true but it's kind of like flying a plane right if you're a pilot you need a certification and you can't fly plane without that certification and for right now data science certification is getting a PhD and then you promptly shooed me away and I was so mad for like the next week and there's actually probably the bottom of what I might have transitioned careers at that point given that experience but I think I held on to the fact that one I feel like I knew that this guy internally just wasn't right in his line of thinking because honestly why would a data scientist with a PhD being charged with like a plane with hundreds of lives right like if a pilot actually fails then their you know their plane is but if data scientist fails they just get fired right so you know not as high responsibility bar right there back to the main point was the fact that I think generally what he was actually getting to and I think this is what I've learned back in the field now with in data science is that it's really hard to trust new graduates and just generally college graduates with understanding the fundamentals of data science where they actually have to deploy one machine learning models or to communicate with business teams on telling them effectively how to fix a product right and as a new grad you don't really have those skills you don't have like the confidence or general like charisma or all this like social networking office politics to be able to convince business teams that you know what to do like you can analyze all this data you have exactly what you know about the business to like move it forward a lot of that takes just general experience of working somewhere right unless but I don't doubt that there are some young people that could do this right now right I think the one thing is that it definitely gets a little bit harder on that side for the analytics and then if you're talking about machine learning models your time out our role that's very specifically geared to I think what the guy was talking about with PhDs right these are are complex fine-tuned algorithms that need to be deployed like in production and run super smoothly so it's like have you ever built a model that could scale to a thousands and millions of users right any requests right so if you think about the uber ride request model how many people are requesting rides on uber right probably like millions an hour even minutes possibly I don't know probably not but in general I'd say that if you don't like how could you ever figure out how to build as a new grad right you need general experience and I think that's where data science kind of was back in 2015 was that they knew that this position was valuable but they didn't trusted to any new grads right and so after that moment I kind of lost a lot of hope so if you go back to my story I lost a lot of hope on generally like becoming a data scientist but I knew that there was all these data science projects I wanted to do and you still knew it was a passion of mine right I was studying Electrical Engineering at the time and I really didn't enjoy it but I found I wasn't actually doing so well we're so hot my major because of the fact that I was spending all my time working on these like data science projects that I like to do and I felt like innately that it was probably more important to me than actual school at that point because I've always been like this proponent about getting experience over kind of academia right and one of the things that I really believe in is having practical valuable experience right and so I started applying to some different internships I started doing some data science projects and these were generally stuff outside of just class right and so I had taken one class on statistics I did a project on predicting like box office movie box office values based on data set and thought that was really interesting and then started trying to see if I could get any data on my own and so that's where I kind of come to point to as a new grad in terms of how you should actually get jobs is not like think about your resume as so much as to primarily sell yourself as an eagerness to learn and an eagerness to actually work on something right and what do I mean by selling yourself so this kind of stands as something as proving that you can do something out of the gate and then to also have an innate curiosity for actual data science and what I mean by that is like how do they know that you're interested in data science because of the fact that you actually like the field versus you just want like some sort of high-paying right and I think that's where you're kind of seeing this transform in terms of these new jobs coming into the market right and where they're very high-paying out of you know just a master's program or like a bachelor's program if you're a software engineer or a data scientist you can make over six figures and that in itself is pretty crazy and I think it attracts a lot of people that are just in it to you know make the money but also there are a lot of people that are just interested in data science so I think one of the biggest and the best advice that I think I could tell everyone to do is to basically to stand out in some sort of way right and this means this means doing something like marketing yourself almost as you are like a product and I'll kind of explain more of that down the line but essentially what I did back when I was back in senior year right was I was doing these data science projects and I was doing them because I was actually curious about them right so I was doing this project unlike and be a data I was doing this project on real estate so I was like walking around Seattle one day I saw a lot of apartment buildings coming out this is in the start of 2015 I was a like okay rent has been increasing miron has been increasing by a hundred bucks every year I bet somewhere else if you weren't just a run out of room if you ran out of actual apartment be increasing by like five hundred bucks per year like why is it going up so much right like which neighborhoods are the most popular and so expecting that I was gonna be in Seattle after graduation I did like a linear regression based on scraped Craigslist data right and just posted it and all it did was it showed every single neighborhood and how much each feature of the neighborhood cost and its base value right so if you didn't actually have any rooms or any bathrooms there how much did location actually cost and this actually turned out to be like pretty fun so I posted that what about my day and then did another blog post I got a few views and I was like okay that's cool and then I did another blog post and I did on the Seattle Police Crime dataset right and this is a data set that is publicly available so anyone can analyze it and I just took it analyzed it did some like cool shiny graphs I made like a prediction model for like how urgent like a call would be and then posted that and then that actually ended up getting picked up by D choir and then Seattle like k2 news or something came and actually on Twitter and just try to interview me because the like the chief of police or something tweeted it out or retweeted it right and so that was great marketing right and after I did that I actually got a ton more internship offers like people saw that news post and they actually wanted to come and talk to me email me hiring managers we're reaching out it is all because I actually got my data science projects in front of an audience right like anyone right now can do something and like write something on kaggle like do like a discussion or like a data science project off of it they can analyze data even that's like super hard to get right they can scrape data analyze it post it somewhere but if it doesn't actually get any views then at the same point it's like it's it's good because you innately you did it and you learned from it by the same time right you're thinking about how you'd be like doing content marketing for a start-up right like you want stuff to get views so that they'll come back and actually look at your product in the same way you want to do blog posts where you actually get some views and then they come to look at your project they see your code they know you can code and they look at your resume and they're like wow this person is actually doing some interesting stuff and I still think to this day given all the different kinds of like boot camps you can do all the different kinds of mentorships you can have I still think that marketing yourself as a data scientist using this method of actually showcasing your projects doing something interesting having an edge and posting it online in like a video or like a blog forum is still the best way to get a job without any experience and I think that is the case because of the fact that is what you have to do to stand out nowadays getting a data science job might just be as hard as it was five years ago given the entire pandemic that's going on right now and given the fact that a lots of companies are tightening up on their hiring for data scientists and software engineers and going only for experienced hires right which means that you have to stand out even more than ever before right there are hundreds there are thousands of resumes out there where people are basically having the same kind of experience they're doing the same kinds of projects and they're just looking for jobs in the same way which is applying to the 80s on the company portal going on LinkedIn going on indeed you can't go through these traditional routes because you're facing with thousands and thousands of other applicants right it's kind of like you're competing in this huge lottery system right many times you only get your resume read if it's like only in like the first 100 right like why would a recruiter go through like ten thousand resumes when they could just you know figure out if they could get like someone good after like the first hundred and first 200 right and so because I you know it's so competitive out there you really need this edge to stand out and I still think marketing yourself more than anything is what it takes to stand out right after I had released that Seattle Police Department data set the funny thing was I actually interviewed for the company that had hosted the dataset it was this company called socrata they did and they still do actually government license out data for the public and I think that's what they did back then but I'm not sure what they do right now but generally they just had all these open datasets right all right it was an easy way for consumers or people that want to didn't want to file like these requests for data to just get access to this data all the time and so the Seattle Police dataset I actually interviewed at this company as an intern for like a software engineering internship got denied after my take home challenge failed obviously because I sucked at coding and then eventually after I posted this blog post and went viral I saw that they reached out again they're like hey we saw that you applied here didn't get it would you want to come interview again and so I come back you're out of interviews definitely fail again because we didn't get past like even like the first module in my line of code when we looked at my take home assignment but then they still offered me the job anyway right because they just knew that I was gonna be interested in like in their projects and that no matter what I would at least produce something that was for anything like marketing value right this is a b2b company that probably gets little to no marketing views when they have this open rich data set which you could just advertise with almost like open journalism type work right and that's actually how I ended up getting an internship for a job that I was originally denied for and so I think this is literally the key that opens all the doors I'd advise everyone to try this method out right I want to finish my last part of the story which is on what happened when I actually got to Java right and so after I graduated I ended up getting a job the startup that kind of went downhill after a few months I'll go into that later but I started at Java as kind of like the first data scientist right and I was actually kind of confused on why why they hired me for this so I had some prior analytics experience experience I got that first Silicon Valley job from my blog post and they really liked it and so they hired me for a full-time role I eventually left that company after four months and then went to Jogger and so the interesting thing about I think Java was that they hired me I think this is the last key point is that you have to really hired me for my eagerness right and they kind of eeriest and learn and to work on projects they knew that like no matter what I was tasked with they could give me like a task and I would happily do it because I wanted to gain experiences so badly within data science and this means the fact that when you have this like kind of eagerness and this hunger to that is literally invaluable because you'll see as you kind of like progress in your career you definitely get more people that are working on different things right they're either learning stuff on management they're doing people management or they're a little bit jaded right they're just doing their tasks they know how to do everything they come in at 9:00 a.m. and they clock out at 5:00 p.m. right and this was a start-up that was eight people and so eventually when you get at that size you need to basically work a little bit more just to stay afloat and because everyone has a piece in the game everyone has equity and I think that to be frank I think before they had hire like a machine learning engineer and they had a fire in the media right because you didn't actually want to work on any engineering aspect somebody just wanted to do data science and build models and I think for the kind of eagerness aspect and for the startup aspect you need to be one hungry to learn and did to do it whatever they take and they throw at you right and then to you also have to be very flexible on what you want to do and your general like learning kind of persona right and this means being able to take any task and work on it if they point at it they say just do this then you have to figure out some way to do it and I think that's kind of like well it's a little bit easier to phrase and to think about after you get on the job you still have to embody that before you go on to an interview right and that's you have to embody that for everything because you're there to actually learn your as a new grad as like a college grad you're primarily focus should always be learning right and I think you know this goes for later on in life too but I think generally when you you know your art you aren't making as much you need to learn more and I think that being able to sell how eager you are to learn and just to showcase and do projects talk to people about it data science participate in data science communities all that is helpful but at the end of the it really is just all about marketing yourself and selling your self and then bodying that character of being someone who's very very hungry for data science and if you can do all those things you'll definitely be fine and I think perform pretty well and get a dative science job and I think that is what I want to talk about next is just how I ended up getting out of data science right but still in data science and starting my own company and I will talk about that next time okay bye

Channel: Data Science Jay

Views: 18,679

Keywords: data science job, how to get a data science job, how to get a data science internship, data science career, data science career advice, data scientist career tips, data analyst interview, data science interview, data scientist interview questions, data science guide, data science job search, data science job interview, data scientist linkedin profile, how to get into data science, how to get into data analytics, data science fresher, data science new grad

Id: 7v_Szio9r3E

Length: 20min 33sec (1233 seconds)

Published: Thu May 28 2020