Funny kilk
Cayy. let's start off with data scientist as a data scientist you're gonna be using your data to discover opportunities and what that means is you're gonna be using your current data to find trends and patterns that are gonna affect the future business that you are working in you'll also be developing analytical methods and machine learning models and most people when they think data scientists think that is the core work that they're gonna be doing and that is actually not true that's actually probably five to ten percent of their job and most of the time they have these models set up that they used over and over and over again so they already know what kind of models they're gonna be using they are just working with the data to put it into those models and then at the end they're tweaking their hyper parameters to really narrow down their accuracy and get better results but genuinely they aren't doing a ton of work in these machine learning models they're not developing new models they're just trying to fit their data into these models to get the best results they can out of them the next thing is data cleaning and when I say data cleaning I mean a lot of data cleaning because genuinely they are doing so much work just cleaning their data making sure it's gonna be good and usable for their models so when they plug it into these models it's gonna give them the best results in the best output and then it's formatted correctly for their machine learning algorithms actually work and actually read the data and give them the output that they want and you'll also be connecting a be testing now this looks very different in different industries but basically you're gonna be doing two independent tests getting two different results and seeing which one actually gives you better results in a nutshell that really is all AV testing is but it can get quite complicated and so I'm not gonna go too much into that but let's look at the data anoles now as a data analyst you're gonna use your data to solve problems that your company has right now so instead of trying to find trends or opportunities for the future you're trying to answer questions that your company has now and have an immediate impact other responsibilities are also creating reports or creating dashboards and for creating reports a lot of times you'll use either sequel or some cloud platform or any number of other tools that are out there for creating reports and then for dashboards you might be using something like power bi or tableau or maybe even Python it just depends on what your company is using I've seen a very wide variety but creating reports and dashboards can be a large part of what a data analyst actually does and often they'll also help with gathering incremental data from different sources so you need the data you have to get it from somewhere so you may work with a client or an internal team to help them gather that data or get that data into your systems whether that's your warehouses are just your Seigle servers or whatever that is for your company but you have to be getting that data somewhere and using that data for these reports and for these dashboards so that may also be a part that you're doing now let's look at the qualifications for each of these positions and let's start out with the data scientist as a data scientist you're often going to need a master's degree or above that can be in anything from computer science econ mathematics physics it really depends on what industry you're going into and what they value but oftentimes those more stem backgrounds are really good for a data scientist now it's not to say that you have to have a master's degree but oftentimes that is a prerequisite for most positions but there are some positions where they're really just looking at experience and your skills to see if you're a good fit and they might take you if you only have a bachelor's degree what's going on everybody my name is Alex Freiburg and today we're gonna be talking about the difference between a data scientist and a data analyst now as many of you know if you watch my channel I am a data analyst but what you may not know is that I actually work on a data science team and so we're going through four main areas today which are responsibilities qualifications skills and then at the very end salary and after all of that I'm going to talk about what position might be right for you so let's start off with responsibilities what kind of things are you gonna be working on in your actual job
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