Get NOTICED in Data Science!!! (3 types of GREAT projects)

Key Takeaways

those types of things really really [Music] uh look the most impressive with companies spending minimal time with your application how can i get more time with the hiring manager it changes that maybe one minute that i'm spending on a resume into maybe like up to five minutes oh what up then nerds i'm luke a data analyst and my channel is all about tech and skills for data science and in this video today i was curious about learning more about how one can stand out in the field of data science we'll be looking at it from the aspect of an employer but i feel like these concepts that we're going to cover today can also be applied to how you can stand out in the community of data science for this i reached out to my friend john who's a data scientist that has both an engineering degree and a master's in data science he has worked the last decade in data science related roles and more recently has acted as a hiring manager in this field most hiring that was happening in north america would go through me for technical evaluations through this role he has found some valuable insights into how to get noticed by employers even before you get to the interview stage really looking at resumes is is a big thing um and looking at the past experience and what they have in a portfolio is really big but before we get into the theme of this video i think it's important to first clear up a misnomer about entering this field a lot of people that i've talked to are like a lot of people that have questions are always thinking like you have to get a degree in data science to start with to get into data science and it seems like it's actually completely the opposite truly the the types of backgrounds you can have to get into this field are so broad but the common thing is just having more computational tools in your belt to tackle all these problems to be clear your educational background doesn't necessarily determine your fit for a job in data science instead it's more about what tools you know and how you showcase them i will tell you that if there's a personal website or probably a github it changes that maybe one minute that i'm spending on a resume into maybe like up to five minutes oh so basically how can i get more time with the hiring manager maybe have this self-designed github page or website that makes you grab more attention yeah absolutely and i'll tell you that um that in in many cases the github or the personal website or portfolio otherwise was a key factor in saying this person's fit for an interview or not the general concept right is that you should have some work that you're readily able to show off okay so let's get into this and understand the strategy and how you can showcase your data science skills in a portfolio for others to better notice this john has a three-level approach for this product in my opinion would be the best uh kind of highest level this is how you make it impressive the the next would be kind of either a blog post a personal website outlining these things or a data storytelling aspect and then then afterwards would just be doing uh the thing we're going to start with the most basic approach and work our way up to the higher levels while giving examples of each so let's start with the scope skill set at a minimum this is how you should be looking to display a certain skill there's two different questions you should ask yourself the first of which is what would be a good skill to show that i know how to do that's that's the first one so whether you're wanting to show off that you really understand uh linear regression inside and out and everything that entails great that's perfect if it's equal great perfect the second thing is um how can i find some way to present that convincing some ways to do that would be do it on a data set that hasn't been seen before great that that shows me that you're not you know taking cookie cutter code somewhere and just redoing it you're having to analyze something new and show that you can take away the right inferences from that data so what does this look like john has his own portfolio example of this so i have on my github a specific link to a repository called data science portfolio and in that if you go there on the read me it'll say hey this folder is where i'm showing the fact that i know how to write good object-oriented code in python so if you click here here's what you can expect this is where i'm showing that off here's where i'm showing out the fact that i know sql and like this is kind of what you should expect if you go in there and then you if you click on there hey well here's you're looking at my object-oriented stuff here's the object-oriented considerations that i want to highlight for you and take a look at this file if you want to see more of this file if you want to see more there's there's a lot of ways to do it where you can uh build in that filtering very easily that just keeps it so simple but then from a hiring manager's perspective it just makes it so much easier for them because then they can go in and verify these skills so much quicker and it just you're setting it up for them to make it so much easier to potentially even get in more and they don't have to like search to try to find this skill set let's now get into the next level of showcasing your skill and that's through the use of data storytelling or a storyline on a next level other than just scoping out neatly hey this is the skill i want to show things that are very impressive tend to have lots of visual elements to them and i'm going to be able to latch on much more clearly to a story presented very well visually so especially interactive visualizations maybe you have a really good tableau dashboard that you put together before a power bi or something along those lines that can be super impactful as well especially if there are lots of interactive elements to that so what does this look like jesse ray a data scientist at apple has a great example of this she took our running data collected through fitbit and utilized python to analyze this data using a blog type format she outlined questions she wanted answered and then went about analyzing and finding these answers to those questions so i think john sums up why displaying a skill in this manner is so powerful it's not just about the code you're writing it's about inspiring the confidence in your interviewer that you're gonna be able to generalize that super well past the direct situation that you're doing finally let's get into the highest level where the goal would be to build a data science product that can be utilized by others products in my opinion it would be the highest echelon because that's what you're seeing mostly in industry data scientists and data analysts don't really work in vacuums they work in the context of either a team where communications need or a product where you need to be able to plug stuff into other stuff but why is john considering this the highest level of displaying your skills it shows to me a ability to think on kind of the next level if you can turn something that's now not just a notebook not just a dashboard but a product that you know it may be in some alternate universe i'm actually selling to people for money those those types of things really really uh look the most impressive so what is a good example of a product a more complicated example would be that of my friend jack who built a fantasy football draft calculator in excel because of the popularity of his excel spreadsheet he went on to build a monetizable application that utilized python and the django web framework all right so let's end this with a quick recap i would say all of all of those kind of three levels the hey here's some neatly scoped skill set code hey here's a good uh data storytelling element hey here's a product all three of those are very good i don't want to give any misconceptions that the fact that you're doing anything is such a big positive as always if you got value out of this video smash that like button and with that i'll see you in the next one [Music] [Music] you