eso. Actually, I recently signed an offer for a data science position, and I work for a company called Toast and they provide tech for other restaurants. And that could be hardware or software. It's kind of like innovation, innovate and virtualized restaurant industry on de. So for me, it was like a long journey into becoming a data scientist. I I started, like so my original kind of my degree. I studied economy, eh, So I started in China. I studied in Hong Kong. Um, and then I switched into finance. I worked for consulting at you. I were deep like a financial advisory and tax advisory for different companies. And eso I'm originally from Pakistan, like, that's how kind of where I started. My first job was in Pakistan, and then I I had this opportunity to move to us for my industry. First, it further because my full time job and my job was a data analyst. I work for a small startup called Fikes. Um, it's a subscription based platform that provides cleaning services, father companies, and for me, it's kind of the first job that kind of started my journey to data and e think I really enjoyed the aspect of, like, really working with different people at the team like marketing team, just to like understand their marketing channels and, like return investment and like Management Team, just do, like, help them understand, like what's going in the company or like engineering team to like, really kind of set up the whole A B testing process and just, like, make sure every change go through that testing before we launch it. And that was really interesting. And I think like working with data. It's like I really enjoyed that aspect and I think for me, it's data analyst Um, it was like, Oh, yeah, I do data analysis and like, what's what's next? What's what's more interesting? So, like, I started studying data science on my own and, um, started going to meet up, so I, you know, I was basis. Yeah, I also like there's a lot off meetups ive enoughto work just like data science related things and like you could talk to people and different data scientists just so I understand how Thio really start off and like, how to switch the career. And I think that was kind of really crucial for me. And yeah, so there are a lot off Also the community of the scientists online. Um, it's it's great, because, like, you could find every, uh, answer to any question pretty much. And, yeah, there's a lot of online courses and, um, there really, really great teachers providing, like, really good. Very well exploration off. Really something really complex. So that was kind of interesting. And yeah, and I think kind of I started since I was working inside up. I was like, Okay, I could actually experiment. So, like, kind of my first model was like, Oh, I tried Thio predict demand, forecasting off oratory, using green innovation. So, like, that's when I kind of realized how, like thats thats model is really working in, like, the effective date of science and like, how? Um, it could be really useful and like, any kind of context and yeah, so after I was like, Okay, I set up kind of a goal for myself, like, Okay, I want to become a data scientist. What's next? And I think I decided to join a would camp, um, like, really dedicate and getting deeper into data science field and like since I had a little bit off a background, like even economy, like had classes and statistics. So those kind of things where can be really translatable into, um, machine machine learning. And yeah. So, like I joined the boot camp, Um, there was, like, a whole class about your mask. Kind of like, uh, check your linear algebra, like understanding off probabilities and things like that. So, yeah, like joined boot camp learned deeper, more about different data science concepts, and yeah, And then after kind of after upon my graduation, I got a job at Amazon. It was kind of screw my boot camp. We had this kind of final presentation where we we're presenting our projects and different, um, companies were attending it. So whether the company was Amazon and that's where I met my supervisor and, um, s So I had kind of a background in finance, and what they do is the team is tax technology, and they're kind of trying thio do a lot of automation within their A team off tax. And yeah, so they're like, Oh, yeah, you have this background and maybe like we can, we can see how can we implementation, learning to kind of use it. And yeah. So, like I started using she learning there. Well, my my work, my job title wasn't like a data scientist, but it was like a hybrid between daily engineering, um, self engineering and data scientists. So, uh, since it was a hybrid, I didn't have, like, a whole all my time dedicated to data science. E think it was more and more becoming more like a social engineering. Like my job style changed into a developer. So I was like, Okay, like, I still want to do this science and like, that's kind of like where I left Amazon and then I, uh, join toes to dio pure data science. Mhm.

site side job for me like I do right thing. Besides blocks for different people. It's kind of ah, way Thio, especially for people who are trying to break into industry to like, we don't have a lot of experience. It's good way to, like show your work and then, um and also show how you can, um, effectively communicate something technical, like data science and, like, kind of write a story about it. So, yeah, like towards data scientists like one of the most popular, Um, you do science blocks and medium And, um, like some. Like I started having a few years ago, just like first published in articles for them, Like send it to them. And then they were, um they need to publish it. And then I just kept going and yeah, like I really liked that aspect of frightening, swell and kind of keeps me Keeps me like moving when I'm not working, for example, and like And also there's so many ways to do interesting projects like you know, about something social, about different social problems, about whatever. Like whatever you're interested, you interests are and yeah, mhm

check are using its python, um on for like but like Python itself, it's not e think it's not enough to like, you know, you need to kind of understand, Like, where do you get your data? Like, how can you, um, use something like a cloud? You know, like a W s like where they restored, like, how can clean it. And also, how do you, like, understand? Like the storage And like the timing and I think form or academia, people use art. I personally don't like I tried learning are, but I don't use ours much, But I think like if you're like if someone's trying to get a job in their science basically like a tech field, it's good. Thio, start learning Python. I mean, it's even better if you know both languages like, yeah, there's like right now there's Julia, which is another language, you know, scientists use, but it's less and less, but I think like it zlook a whole thing of like, How do you differentiate yourself from other and what makes you a bigger scientists and other like, How would you get that job with all those? Like I don't know 700 people who applied for that position. So it's because it's constantly changing. So there, like so many tools you need to know and also like with even with working with data like something like Spark, um, like you need to understand how it works and how it works in Python Pipes Park and, yeah, things like that.