 Hello everyone and welcome to another episode of Code Emporium and today we have a special episode. As you all know, data science opportunities has been skyrocketing over the last few years with tens of thousands of professionals in data science from across the globe. It's an extremely fun field which is abound with opportunities and so today we're going to talk about how you can potentially get a job in data science. Full disclosure, I have about two full years of data science experience under my belt and I'm hoping that my experience can help you land that data science opportunity. So let's talk about the two major ways of breaking into the field. The first one is that you're transitioning into a role while already working on a non-data science role within a company. Engineers, analysts, data scientists, all of us use different tools but at the end of the day we all solve problems. This is a rough illustration of how problems that data scientists solve overlap heavily with that of software engineers and data analysts. This is further evidenced by the fact that data scientists work really close with other sectors of an organization including sales and marketing and because of such a major overlap in backgrounds almost any background that you have will only help you as a data scientist and we even see that this is true statistically. Because of this here's some advice I can give you if you're looking to transition into data science. The first is revisiting problems which really shouldn't be a problem if you've already been working but what I mean here is that you should take a step back and try to redefine the problems that you may have already potentially solved. Try to write the definition of your problem more concretely and also more concretely define what success really meant from your perspective and once you've done this thought experiment you can look into the second piece of advice and that is framing problems from a data science standpoint it's essentially taking the problem that you just laid out and identifying what were the inputs what are my objectives what are the outputs what is success and how do I quantify it all of this from the perspective of a data scientist. This thought experiment can help you look at these problems from the lens of a data scientist and you can further add context to this problem with your own understanding with your own background hence any experience you have here will only help you. Now the second way to get into data science is straight from college. Multiple studies have shown that 70 to 90 percent of all data scientists hold at least a master's degree as of 2020. While it may be hard to land that job with a bachelor's degree it is certainly possible and here's some advice that you can follow to increase your chances of getting that data science job. The first is to know your fundamentals just understand a little bit of sequel know a single programming language and also the basics of some probability and statistics. You don't need to be a master here but just at least know the basics enough for you to do the second point of advice which is to take on projects end to end. Data science is all about solving problems and so you want to simulate the idea of problem solving by taking up projects end to end. It's actually a great thing to talk about during interviews and is probably the most valuable thing you can have on your resume aside from actual work experience and academic papers. The third and probably the most important piece of advice is to always be eager to learn. Data science is an evolving field and we need to be able to evolve with it regardless of what our experience level is. The moment that you stop learning is the moment that you fall behind the curve but hopefully you won't because the field is super interesting. As for closing thoughts here transitioning into data science by switching roles might be a little easier since you already have an understanding of how to solve problems and you've even solved some of them before and so working towards data science is mostly just changing your perspective of how you look at these problems. You don't have to worry too much about the tools and technology although it does definitely play some role. As for transitioning from school it is true that 70 to 90 percent of data scientists hold at least a master's degree but this also means that a high 10 to 30 percent of them only at most hold a bachelor's degree and so this means that it certainly is possible to get into data science even with a bachelor's degree. Just know your fundamentals and make sure that you're working on projects that really interest you. You need to make sure that these projects are definitely fun to work on because that will make you eager to learn more about the concepts and actually complete the project and that eagerness to learn is one of the most important aspects of being a data scientist and I will leave it at that so thank you all so much for watching please leave a like subscribe for more amazing videos on data science artificial intelligence machine learning and I will see you in the next one bye bye