3rd Year Statistics, Data Science, Computer Science Resume | Reviewing Your Resumes Ep. 1

Key Takeaways

hey rachel how's it going wow how about you pretty good pretty good so yeah like thanks for agreeing to you know showcase your resume to the world even though it has been anonymized and we're gonna go through first of all like what it is that you want to be applying for right and how we can tailor your resume for those exact applications and also just like some of my general comments on how you can improve it does that sound good yeah so before we do that you want to give just like a brief introduction about yourself so yeah i'm rachel i'm currently a third year student at cal poly san luis obispo and i'm studying statistics and data science and i started a youtube channel around a month ago meant to like bring together a bigger community of data science students and educators and professionals and i'm still learning a lot and really excited to do satina she definitely has a lot of knowledge and is going to help you guys out a lot and me as well cool awesome all right should we get started okay so let's talk about like strategy what do you think you want to be applying for yeah so i am definitely more interested in applying to more like data science specific roles as well as like some software engineering positions um this is my first time applying to more technical positions so i'm kind of like casting like a big net but definitely do those two areas cool cool so both software engineering and data science first thing in terms of that strategy the best way for doing this is having like a master list of like kind of projects or things that you can't put in your resume have it like on a google docs or something like even microsoft word something really simple so you can quickly cut and paste stuff in uh that you need so that you can tailor that for that specific role like for example you can have lots of software engineering role projects and you can also have a lot of data science projects and if you're applying for data science then put in all the data science lab you have software engineering put all the software engineering stuff and that should be pretty quick because the template should be the same so yeah like i really like the the color like it definitely catches my eye statistics and data science student tells me like who you are and what it is that you're interested in like you're a second year statistics major with minors in data science computer science passionate about machine learning data communications always seeking new opportunities with within data science and software so i would condense that into one sentence so it's like really pops out so i have a really good idea of exactly who you are and what you're doing that makes sense and i forgot to change it i'm a third year not a second year but i'll fix that later let's see so technical skill set i love that python java are sql numpy pandas all these things again um if you're going to tailor this like depending on if you're going to go for software engineering or data science change the technical skills so if you're going for software engineering um probably don't need to put a b testing probably don't need to put pandas machine learning text mining things like that but you can put more stuff like object oriented programming for example okay okay moving on education right that looks good it looks fine to me uh relevant coursework so in terms of your relevant coursework try to condense that again um so if you're going for data science then your relevant course book should be data science stuff if you're going for software engineering then software engineering things and i would say like try to minimize the amount of relevant coursework to like three maybe four because this is just like kind of it's amazing like you clearly have done so many technical like technical courses but i kind of get a little lost just trying to read through them projects nlp analysis of bay area bogoshop great love that use datascape with a yelp api to analyze reviews sounds good use nlp methods to cluster together similar words and categorize global shops based on similarities or reviews okay so for this one you know i love how you tell me um that you scrape the data and then you use nlp and what you what and what happened for that but you told me like what happened to that analysis right like did you use that to like change like increase sales in in in boba's jobs like or it could just be like you know you were able to figure out which ones are the best phobia shops you know like what's the impact of what you did okay that makes sense machine learning model predicting car price i think my cat is there his name is beep beep yeah bp and my other cat is called boop yup anyways okay there's beep beep let's go back to the resume um let's see machine learning model predicting car price so i assume introduction to data size this is a course that you took is that correct yes okay okay cool i would say like put the course code on not because anybody cares about the course code but then i would know that it's a course okay implement a four layer in your own hour to predict the price of the car so again similar to the nlp analysis amazing how you told me like what you did in a very like simple language so completely understood what you were doing and i also knew how good your model was but again try to like drive from that impact a little bit so you predicted the price with a 100 degree area why does that matter right it doesn't matter because um like it could be used to figure out like what car prices are going to be so you can sell at a higher price or when is a good time to buy a car interest in hobbies cooking rachel eats that sounds pretty awesome going on here work experience data science intern pg and e so when you say present it means you're working on it right now right yeah i would say put a date on maybe like july 2020 and just and then just put like a dash so we know that it's like continuing on okay so one thing i noticed is that your tenses tend to interchange a little bit so it's for example here use like used used implemented compare these all past tense try to stick with one tenth so if you're going to use past tense so you try to use past times with everything okay that's just kind of like sorry because i've just heard like um i've heard the thing about like keeping the tenses the same but when it like does it flow better like present versus past tense yeah i think past tense works the best um even if you're talking about the present um and also another one like try to vary your like first word a little bit more like it doesn't really matter that much but it's kind of like a little boring if you just see like working working repeatedly that and try to make it like more exciting you know like create it you know like impacted things like that so it's like more action-driven as opposed to just passively working on something because it makes it sound like you just had to work on it right i love the second bullet point created data models in python are using heat maps regression analysis and other relative visualizations like that tells me exactly what technology that you use and what it is that you did for the first one um i think it's fine the way that it is but if you really want to drive that home and make that better try to make me like understand again like what like what does this work actually mean right like for me like looking at it right now i don't know what pg e is so maybe that's just me like i don't know what the company does and when i read electric business operations team analyzing aged orders based on efficiency and effectiveness i'm not exactly sure what that means but yeah if you can like make that so that someone who doesn't know what pg e is and is not familiar with this industry in general is able to like understand on a high level what's happening that would make it much more engaging and also you probably know what pg e is pacific gas and electric they manage all the actually you're not in the pacific so maybe you don't i'm also not american so maybe that's another thing yeah it's just they manage all like the electricity the water like all of that stuff um okay okay it's fine the way it is but if you like come across super clueless people like myself that could be like useful to have yeah data engineering research assistant cal poly engineering present yep so we talked about like the present thing yeah i worked under to analyze neural network models on accuracy and precision in order to quickly classify marine animals and underwater footage that sounds really cool and that that like immediately captured my intentions i think that's that's really awesome yeah i don't really have that much to say about that for data analyst research assistant that looks pretty awesome to me as well okay youtube i would put youtube under projects okay yeah i think second bullet point is amazing because that really like brings out what you're passionate about statistics workshop leader is this part of your university yeah okay okay yeah so maybe just write like cal poly academic skill center so i know like uh like where it is that you did this that looks pretty good facilitated over 30 students a week through self-plan workshops for introductory statistics courses sounds good yeah and leadership so director of external relations network with other chapters in california to host networking social events worked on yeah so again like just like a i don't want to sound like a broken record but just like generally try to think about impact the way that i usually structure um like one section is first higher level description of what is happening so that's someone who has no idea what your industry is or what your project is knows what you're talking about second one is describe like throw in like python r you know those like technical things that you did and then third one is if you have a third one where you can also integrate that with your second one focus on impact like why does that matter why is your analysis matter like you now worked with other chapters and you worked in executive board like what came out of that did you like um create an event right did you have a speaker did you help people get jobs yeah yeah okay yeah and that makes a lot of sense i feel like i've been focusing on like what i did and how i did it but not the impact of it um okay that makes sense yeah yeah for sure and um just like as a note i assume that you also did like some software engineering projects like in some of these classes right so when you're writing um the projects for software engineering definitely focus on a tech stack um i would actually have just a separate bullet point that was something like tech stack where technologies use colon my cat is here again hello so actually so i should make it clear in the description for those projects like what language i use them so right now like you would have like use natural language processing methods to cluster together similar words for example right for um like in your nlp project or in data science for software engineering i would just be like very specific like technical stack or technologies colon and then just list out the technologies that you've used okay okay i'll do that so i think it looks like i'll probably have to make two separate resumes one for software and from data science and then like specify um my coursework and projects for that okay yeah yeah for sure i think i think that would be best and like i said earlier have that strategy like stick everything into one uh like just trying google docs so you can cut and paste like whatever it is that you need for that specific job because i assume that you might be applying to some jobs with like slightly like hybrid job descriptions like maybe like data engineering positions then you kind of like want to mingle together a little bit the data science and the software engineering okay yeah okay awesome i had another comment um which is the fact like like i said i love the coloring like the the design is like on point um my only comment about that is like this would be great if you're going for like tech um where you're going for somewhere that's like more like artsy if you're going for like something that's more traditional especially like finance banks they want something that's a little bit more traditional as well so in that case uh the best thing would be just like have a pretty boring resume you know you know what i mean by that right like literally separated by lines no color black and white that's like kind of the industry standard for like finance and like more boring industries so it's much safer to go with that like not that having like a cool resume is bad if someone is just like a very traditional person they're like oh my gosh like this there's like color on this like i can't handle it like you don't want that to be the reason why you don't get an interview oh wow okay so then i'll make three copies of resumes now okay yeah yeah i mean that should be easier to make than the other ones because you just like get a template and just stick it on right and like you don't have to do like any of the formatting and stuff um also if you have a resume like that you can put more stuff in so you can like stick in another project just because of the way that the spacing is yeah okay got it i just wanted to ask about software that like where you enter where you submit your resume and it's the it's the first thing that sees your resume and like kind of scans for the keywords and everything so like hearing that like like they're just the standard resume templates those are the best because those are the most like so yeah for sure for sure that's actually another reason why i suggest like having a more traditional resume especially if you just make it on microsoft word it's very very easy for these parsers to do it very well if you're going for tech companies you're usually better at parsing stuff so it could be okay but it might not be worth it to risk it um even for tech companies for like finance industries and things that are not very tech specific that is definitely going to be a problem for them also the reason why i suggest that having like the tech stack like writing exactly like what things that you use is because they often scan it based upon these like buzzwords these keywords and if you have like a bunch of them that counts as being good okay yeah so do you have any like questions for like things that maybe i can explain a little bit better yeah i yeah i don't think i have any questions you you went over a lot so yeah i think that if you did that everything will look great yeah because it you it's already like done pretty well like there's nothing when i'm looking at it i'm like oh like it was this is something that we definitely need to change i'm more like nitpicking at specific things and just kind of elevating it to the next level is your resume just like the standard default like um like type of resume mine is a standard resume mostly because i didn't want to risk the parsing thing that could happen and also because i was applying for some traditional roles in finance and i didn't want to risk someone being extra traditional and not liking my colors and stuff okay cool okay got it so i hope that was really helpful for you feel free to reach out to me again if you have any questions or maybe you update your resume i'll be happy to take a look as well let me know if you enjoy this style of video where i talk through a resume um that's a bit more personal so instead of just reviewing a resume by myself i try to have a conversation so the other person knows like why i'm making the suggestions that i'm making check out rachel's channel which i'll link above and also in the descriptions below if anybody else wants me to do this kind of video with them where i go over some resumes send me an email if you like this kind of content please remember to like the video and subscribe to the channel i just started making youtube videos so every single like every single subscriber every single comment really means so much to me and encourages me and motivates me to make more videos for you guys thanks for watching this video and i'll see you guys next time