138: Steven Tran’s 3-Month Journey to Becoming a Data Analyst

All right. Very excited for today's episode. It's actually an interview I did with one of my students, Stephen Tran, who is a member of the data analytics accelerator. Um, I, or. I've already published this. You guys have maybe heard this before, but I really just wanted to highlight. How incredible Steven's journey was. And for those of you that are new to the podcast, you might not have listened to this one. Um, because it was quite a bit a while ago. So, um, And we just kinda went through Steven's whole story of how he actually landed a data job kind of step-by-step and. I thought this was a great episode. I just wanted to reshare it with y'all if you haven't heard it. So, uh, let's get into today's episode. Welcome back to the Data Career podcast. I'm super excited for two. Today's episode, I'm doing an interview. With one of our DCJ Data Career Jumpstart members, Steven Tran. And I'm super excited to have him here and tell us about his story. Welcome to the Data Career Podcast, the podcast that helps aspiring data professionals land their next data job. Here's your host, Avery Smith. So Steven, welcome to the podcast. Thank you, Avery. I love that you invited me on the podcast. Cause I don't know if you know this, I've listened to every single episode of your podcast. Have you really? Yeah, it's actually helped me a lot making my LinkedIn posts. So we'll talk about that. Awesome. Well, now you, I guess this is one of the episodes you won't listen to. You don't have to listen to this one. I guess you can just, you can just be in it and you can just talk about it. So super excited to have you. So let's start with, we're gonna start with the big picture. Okay. So for those of you who don't know, which is probably a lot of you guys, Steven. What was your title before your current title? It was technical support analyst. Okay. And what type of company was that for? It was for a mortgage company called Ellie May and they were acquired by ice mortgage technology. So that's what they're known as now. Okay. So you were kind of working in this like mortgage company doing a little bit of. Of it work. Is that right? Or yeah, I, I just call it a glorified tech support job. Okay, sweet. So like, was that like making sure people like had PowerPoint working correctly or like, what was like a daily task? Yeah. So it was a little bit more than that because what I was doing, I was giving like API support, so we have our program called encompass where people can, our mortgage loan officers can go through and manage their loans and stuff, but we also we allow them to create their own code. So I would help debug that code for them basically. So I would have tickets and whatnot that I'd have to go through and follow up and you know, and all that stuff like that, but yeah, basically a tech support role. Okay. So from a tech support role to now, I think you're. Title is, I'm going to read this, Senior Associate in Analytics, right? Yep. That's correct. Okay. At Dentsu, which is like a, like a big media marketing company, right? Mm hmm. That's right. Okay. So basically you transformed your career from this tech support role into this, you know, senior associate in analytics role in like less than six months, correct? Absolutely. Yep. That's right. Okay. So to give the people a timeline, you are at this non data job and then got this awesome data job in just a couple of months. What were the timelines on that? Like, when did you start your data? So in data journey overall, I finished my degree in business administration back in December. So I was looking into jobs of data or like how I can gain the skill set in November. It's been a very recent pivot. Cause I was kind of like, Oh no, I'm going to graduate soon. What am I going to do? You know, I'm working this, this dead end tech support job. I don't want to do this forever. I want to be a data analyst. What is it going to take to become one? Okay. So I didn't realize that. So this is November of 2021. You're going to graduate from your degree, which was in business administration in December. And, and that's when I guess you spoke or to a mutual friend of ours, I guess your cousin. Is that right? That's right. Okay. Dom, shout out Dom. And Dom introduced you to me and in my program. So I think you joined Data Career Jumpstart, the big course, the project camp in November, correct? That's correct. And then when did you land your job with Densive? So my official start date was February 28th, but they extended the offer to me about a month beforehand. So January, like the end of January. Okay. So, so end of January, early February. So basically we're looking at November, December, January, January, three months. Yep. Three months from, from like, did you, like how much data experience did you have? So. I had Python classes because I also did computer science before I transitioned. And I also had a single SQL course that I took, which I did not take seriously, so I didn't carry a lot. So, not a whole bunch, I would say. Okay, but some. So that's, that's what you're referring to. Back in college, you originally were studying computer science and then switched to business, right? Yep. So not like a ton, definitely no real world experience, you know, maybe some college classes and you were in a tech support role and it sounded like there were some, at least looking at code involved in that. So not like the furthest away, but also not the closest, right? Yes, exactly. Okay. So basically just, just to give people an overview in three months, you went from tech support role to this new job in analytics, and I guess, tell people a little bit about your current job. Like, are you in the office or no? Nope, it's completely remote. Completely remote and like, do you like what you do more than you did previously? Oh, absolutely. 100%. It's, it's so much fun. I'm learning so much every day. I mean, it's stressful with all the projects that are going on, but it's, it's good stress. You know, it's something that I can work on and learn more of. Okay. And like, so, okay, now you're working remotely. I guess you're still in California, right? Yes, that's right. Okay. So you got to stay where, live where you want to live. The people, the, the company density is pretty international. Where do they have offices? I don't even know. They have a lot of offices on the East coast. I, one of their main offices is in New York. So a lot of my team is in New York. Do you have to like wake up early for calls then? No, actually they've been pretty nice. Even though I'm the only West Coast person, they've been trying to schedule all our meetings like later on in the day just for me. So it'll be in the afternoon for them, but like in the morning for me, which I don't mind at all. So they've been really nice about that. That's awesome. Okay, so you get to be where you're at. You're a West Coast guy. You're working from home. What, what about financials? Like, like, are you, if I've been going to as much detail as you want, but like, do you feel like you're better financially at this place than you were at the other place? Yes. 100 percent in a better place. I wasn't struggling before, but I definitely not struggling now. It was about a 15 K increase, which is I'm super psyched about because this is something that, you know, I like living on my own. I want to keep living on my own. So I've am able to do that still. Okay. So, wow. So basically. You like essentially in three months, you gave yourself a 15, 000 raise basically. Yeah. I would say that. And, and the cool part, I think about analytics and data in general is it's like, you're not, it's not dead end. Like you can keep progressing on and on for a long time. So it's like, you know, it's 15, 000, you know, at the jump. And then, and then, you know, maybe five years down the line, it's another, you know, 20 or something like that. Who knows, but it's like, you can keep progressing. Right. Isn't, I think that's one of the coolest parts. Yes, that was one of the biggest things for me because one of the things that I asked for when I was interviewing was that, do you have a way for me to become a data scientist? Because that was a really big thing for me because progression is huge for me because I need that motivation. I need to be able to progress upwards and you know, it's not just from a money standpoint, it's from, I just want to build myself. You know, I just finished college and it's still fresh for me. I want to get into the workforce and I want to build my reputation. So let's now, now, now that people understand, you know, your journey. So from tech support, graduating college in business, maybe taking one, one or two programming classes to within three months. Landing this job at a pretty big international, you know, marketing company, getting that 15, 000 raise, being able to work, you know, where you want, let's talk about kind of the, the, how, how you got there and what you thought was, was important. So you started by joining Data Crew Jumpstart and. You know, took some of the lessons there. Do you feel like you were learning quickly? Like what, what was the first thing that you're like, Oh my gosh, I'm getting this. I like this. Like, what was the first time where you're like, this totally is something I want to. Yeah. So definitely the biggest thing that I love about DCJ, and this is one thing that I talk to a lot of people about is I like the project approach rather than the, here's a homework assignment. It's due next week kind of approach. And also the, the shorter videos, the bite by bite, 10 to 20 minute videos. I don't know about you, but I feel like. I just snore an hour, two hour long lecture. Like I don't retain anything, you know, and a lot of these things, they are hands on. You can follow along, but I just get so bored. I'm gonna have to pause it here. When I come back, I'm gonna forget where I was. So I love the little bite sized videos that you have. And that's just one thing that was able to keep me to do like, Oh, maybe I'll do two videos today or three videos next day. So I can just do something every day, you know, it keeps it fresh. Yeah. I think that's something I've really tried to do with most of my courses and trainings is like projects, projects, projects. Projects, projects, projects. And I remember, I think you latched onto that pretty quickly. I remember, you know, one of the hobbies that you have outside of data, right? But outside of work is, is weightlifting, right? Do you want to tell the people a little bit about what you do? Yeah. So I'm a competitive power lifter, which means I try to lift as heavy as I possibly can in the squat bench and deadlift category. So that's a little, fun thing that I do outside of work, outside of my nine to five, outside of my studying. So I, you can typically find me at the gym, maybe two to three hours a day. Okay. But don't, don't be humble. Tell the people how you did in the last competition. Yeah. So I ended up getting a gold medal first place in my last competition. So that was really fun. And how was it? Come on, give us the details. So squat, my heaviest lift was 457 pounds. Let's see. Bench was 270 pounds and the deadlift was 500. 2 pounds. Sheesh. That is crazy. Yeah. I don't know if I've done that, that much weight, like in all of my years combined of, of going to the gym. So anyways, you, you love weightlifting. You went through a pretty big fitness journey in your life too, right? Yes. Yes. Yeah. And I remember you made a project about it, if I'm not mistaken about. You know, kind of your weight loss journey, your, your weight increase and like being able to lift. And for me, that was when I was like, all right, I see big things coming from Steven. I was like this, when you're able to take something in your life that you enjoy and apply it and tie it into data, I'm like, okay, that person's going to succeed. Absolutely. That's one thing that I talk to a lot of people, a lot of people that have been reaching out to me through LinkedIn is just don't just do these projects that people are telling you to do. Learn those skills and apply them to things that you're passionate about. Because I had so much fun making that dashboard. Like, I don't know about you, but like, if someone told me I had fun doing dashboards, I would be like, You're just a nerd, dude. I don't want to hear this, but I had so much fun doing that project because it's personal to me. It's something that I care about. And I just wanted, it was my baby. You know, I wanted to make it as best as I could. And people loved that dashboard, especially during interviews. Yeah. So, okay. So you're in DCJ. We're doing projects. So we start off with the screen time project, doing a lot of data visualization. Then, then we have a project about fitness as well. So we dive, dive into Python and those are kind of the, the two, the two things that probably you had done before applying to jobs, is that correct? That's correct. Yes. So it took you about. Two months to do those more or less. Is that right? More or less. Yeah. About two months. Okay. And I guess another aspect of DataCrew Jumpstart is it's not only technical skills, but it's also, you know, personal skills and soft skills and networking skills. So whole section on LinkedIn, whole section on finding jobs when you were applying to jobs, what was your strategy? And then what ended up working? So when I was applying to jobs, a lot of it was just. Going on LinkedIn, looking for data analysts, whether I was, I was filtering by remote because my last job was remote also. And I was like, I don't want to go back to office anymore. I can just leave and go for a walk whenever I want to. So I made sure remote was one of those. And then I also did easy apply. I know it's not like the best way to go through jobs, but for me, I needed to do job applications as easy as possible because it's really draining to do job applications, especially if you have to email like three different cover letters or whatnot. So Easy Apply was really good for me because I can literally just lay in bed, watch Netflix and just apply, apply, apply. Okay. I get through like 50 or so applications a night. You know, just chilling, applying that way. And yeah. Did you have any luck with the easy applies? I'll be honest. Not really. I had one company get back to me, but that's because I had experience in the mortgage company. So that one company got back to me and I did interview with them as well. Okay. So a couple of things, a couple of things that I think you said, one is like you're applying to like data analyst positions, correct? Yeah. Two. Yes, that's correct. Okay, so one thing I like that Stephen just mentioned, he doesn't have, he's never been a data analyst, he doesn't have analytics experience, he's never been a data scientist, but he's applying for these entry level, you know, data analyst jobs, but where he had success, I think is really important here, Was when he applied to a mortgage company. And some people are like, Oh, I don't have any experience being a data analyst. And you know what, that might be true. That might not be on your resume, you might not have actually crunched that much numbers, but you definitely have some sort of experience, whether it's in teaching or whether it's in mortgage or something like that. I think it's important to really marry those at the beginning, especially when you're trying to get interviews, because like, There's data in every industry around the world, right? If you've been, you know, it's, if you've been an athlete, there's, there's sports analytics jobs. If you've been in business, there's business analyst jobs. Like I think Steven did a really good point there of like leaning in on his, you know, background. I think that made him more attractive to, to employers and recruiters and stuff like that. And also a lot of perseverance right there, you know, cause, cause I'm sure you got a lot of projections and, and didn't hear back from a lot of those, right? I'm still getting those rejection emails and I'm like, I'm good, man. I'm almost three months into this job. I don't, I'm good. Yeah. Yeah. You're like sucks to suck. I already have a job. Thank you very much. So let's talk about that. So how did you find this job or how did they find you? And what was that process like? Sure. Yeah. So I actually saw through the DCJ discord, you know, Ellie, I absolutely love Ellie. She's one of. My mentors and Avery, you're also one of my mentors. I want to make sure that that's clear like You have an amazing community that you've built here and the people that are giving back even though they're not We talked about this which is really funny. Yeah, and I wanted to message her on linkedin, but she did not allow People so I had to get in mail and to get in mail I had to get the was it called the LinkedIn premium Yeah, I literally paid 40 just to get LinkedIn premium so I could send her a message and say hey, I'm interested about this job Can you look at my resume? Can you talk to me? Let me know like would I be a good fit? What do I need to look for? To learn to be a good fit. And we scheduled a phone call and we talked about all of that. And she actually helped me rebuild my resume. She helped me highlight some words and stuff like that. I would, I would go as far to say that she did, redid my whole resume for me. She was giving me tips at first and she was like, you know what? Just send me the, send me the word file. And she, she redid my whole resume for me. So she's absolutely amazing. She's a star. Senior manager of analytics in Dentsu as well. We don't work on the same team, unfortunately, but we still talk from time to time. And she's an amazing asset to have in this industry. So I think, I think there's a lot of really interesting things there because part, part of the reason I made DataCrew Jumpstart, and I haven't really, I haven't really talked about this since I launched the course. I've kind of, I've kind of forgotten about this, but one of the reasons I launched it was because, you know, I, I broke into data science, like. Like seven years ago. Right. And when I was doing it, I mean, it was, it was still pretty popular, I think, but definitely not as popular as it is now. And there definitely was not nearly as many resources. And I was super lonely. I was like, I don't know if anyone knows what I'm doing or like, I don't know if anyone else is on the same journey as me. A shout out to Ellie. Ellie is totally awesome. Very helpful to the community and aspiring data professionals. And you connected with her, but, but hold on. I, what I love here is that like. There was a, there was a something to yet overcome. You like couldn't figure out how to message her. That's okay. Cause cause you paid the 40 bucks. You got the LinkedIn premium, sent her an email. What was that cold message? Like, like, just like, Hey, I saw you posted in DCJ discord. About a job opening, you know, I've been, I've been an Avery's program and learning something like that. It was 100 percent just like that. It was just, yeah, I've been working in DCJ. I've been, I've done with most of it. Can you look at my resume? What can I change or what should I learn? What should I focus on basically? Yeah. And I love, I love that also because you had a portfolio. That's, that's something. That that. Okay. So I have a lot of DMS. I get a lot of DMS every day. People, people asking me for advice, people asking me for jobs. I get a lot of jobs. It's, I think one out of a hundred DMS that I've ever gotten have had a portfolio attached to it. And guess what? Guess who I hired as the one person I've ever really hired is the person who had a portfolio. Having a portfolio just proves that you like are for real and like you can do the things that you say you can. Here's the evidence, right? And I know Ellie really liked that about you that you had the portfolio. That like you had evidence, she's a big fan of data visualization. You had awesome data visualizations, for instance, from, from data career jumpstart and also just like your fitness journey and stuff like that as well. Had some, had some pretty cool data visualizations. So I think that played a big role in you, like catching her attention and her being willing to help you out was just like, you were for real, you know, that portfolio made you for real. Yeah, I was gonna say portfolios are very undervalued right now because I, I also get a lot of DMs, especially now with all my posts going viral or whatnot, but a lot of them, they don't have portfolios. Like they don't send me, I ask them, I always say, Hey, I can help you. I know you're looking, send me your resume, send me your portfolio. A lot of them don't have any portfolios. And I just keep telling people like, how do these companies know what you've been working on? Sure. You got the SQL skills. You got the Python skills. Data visualization, but they need to see something needs to be tangible. They need to be able to picture you in their role before they hire you. Yeah. That's one thing that I try to promote. Yeah, for sure. And let's, let's go ahead and talk about your LinkedIn. So I'm actually, I'm actually going to go ahead and I'm going to go to your LinkedIn right now. Cause I want to, I want to get some live, some live things. All right. So I'm going to linkedin. com. We'll have Steven's LinkedIn in the show notes down below. I'm going to go to your page. Let's see. I just lost it. There we go. And I want to check something. So currently right now, you have 3, 831 followers on LinkedIn. Okay. Yeah, I want you to go back to November, six months ago, okay, not even half a year really. How many, how many connections or followers did you have on LinkedIn? So I had zero followers cause I didn't allow followers and connections. It was probably like 20, like 20 people. So basically you've grown your LinkedIn, like who knows how many times since, since you joined DCJ basically. And, and, and more specifically. So you went from, let's say, let's say from 2020, I hate how LinkedIn has like connections and followers. It's kind of confusing. I'm just going to call them followers. So you had like 20 connections. And now you have 3, 831. Now let's, let's talk about specifically how you gained those. So you've been posting, I know a big part about DCJ is posting, posting, posting, posting, posting. And recently, let's see a couple of days ago, you had a post go super viral. Five days ago, it has 3, 194 reactions. 95 comments, 57 shares, and it's three sentences. That's right. So did most of the followers come from that or before that? I would say most of them came from that, but I wanted to make sure that I was still posting after that. Because I feel like when you get that exposure, it only lasts so long. So the biggest thing I wouldn't say stressor for me was like, Oh, what's the next post going to be? It's definitely not going to be as good, but I need to show these new followers, you know, the type of content that I want to put out, the kind of things that I want to set. So it was a little bit of a time crunch for me. Yeah. Okay. So then the next one was three days later. And, uh, it ended up getting 872 likes, 82 comments and 25 shares. Yeah. Yep. That was the things you can do to break into data analytics. Okay. And then the next one had 1, 437 reactions. 85 comments and 163. That's right. Okay. So gone pretty viral recently on, on LinkedIn. People are asking you for advice. What, what advice do you give people who, who said they want to go into analytics? A lot of the time I will ask what their background is because a lot of people, I, you don't necessarily think that you need a background in data analytics. You can literally get started today. Like look up SQL, look up some Python, learn some data viz. But a lot of the times. They're, they're asking like, what can I do or what can I learn, but some people are just straight up asking me for a job and I'm like, I mean, I'm just a, I'm just an associate. Like, I can't, I can't give you a job, but some, actually some people ask me like, Oh, do you have any projects I can help on? Those people, I value their comments a little bit more because it's not asking for a handout. I don't want to sound vain, but it just seems like it's not mutually beneficial. beneficial to either of us, you know what I mean? So I like those messages that people are asking like, well, what are you working on? Or what, what can I help you with? Things like that. It's, it's, yeah, I totally agree that whenever, whenever you're, you know, cold messaging someone or, or even like talking to someone, it's a, The first message should always be, how can I provide this person value in their life? How can I help this person? Because, you know, obviously, you know, I have a substantial LinkedIn following and when I have posts that, that go viral, it's like a mad zoo in there. It's like very, it's very crazy. And to be honest, I don't read like half of them probably at the end of the day, it's just, it's just too much, but I try to find the ones that like, Oh, this is interesting. Or this person's different. Or this person is saying, thank you. Like this person doesn't want anything from me. They're just saying thank you. And yeah, maybe it does seem vain, but that's like human nature. Like we, we don't trust people until they prove their worthiness, you know? And most of the time people are just asking for stuff and it's, it's kind of annoying because unfortunately. I can't spend, you know, we can't spend our whole lives and our whole time helping people. We can help a few people, but when it gets to such a big, big number, it gets a little bit difficult because we got to put food on the table. Got to pay the bills. Yeah. So let, let me actually, let me, let me read this, this viral post that you had. So let me pull this up here. The one I really liked was things you can do to break in a data analyst. Learn your hard skills in order of importance. I am a SQL Excel. Python, statistics, data visualization, Tableau, and Power BI. Learn your soft skills. Tailored resume, online portfolio, answers to basic data analytic questions. And then don't forget to apply. Okay, so talk about one of those points that you find that's like really valuable that other people maybe, maybe don't see the same way that you do. So, um, Yeah, this, this post was definitely built on my experience trying to get a job in data analytics, which I feel like my individual experience would also apply to a lot of other people, which a lot of people have been sending me messages like, hey, I've been in the exact place where you are, except I haven't gotten that job yet. But the biggest thing that, the main reason I wanted to make this post This post was the just because you don't satisfy the job requirements part. There was actually a podcast that I listened to you and someone said this. I'm sorry. I'm forgetting the name of the person that you talked to. I think they were a data freelancer, a data freelancer. They were talking about that. Just make sure that you apply. Like a lot of these job requirements are just like, they're not even minimums. I don't think they're like the ideal candidate. And that really resonated with me because when I was applying to jobs, um, A lot of the time, I wasn't even looking at the job requirements. I was just applying, because like, because in my head, I'm just like, if they considered me, then they fit me as that profile. So if, if I might as well shoot my shot, right? For sure. So that was, that was the main thing I wanted to nail home. It's just like, these are like, if you fit 50%, 60 percent of that profile, do it. Why not? What do you have to lose? Yeah, especially if it's if it's only time I mean, and time obviously is valuable but at least it's not money you know what I'm saying like you can apply and definitely like I think, I think the requirements have to be honest so I obviously I try to help people find jobs and so one of my one of my main jobs is to try to help my students, especially inside data career jumpstart. Find jobs that fit them well. And so I spent a lot of time talking to CEOs, a lot of times speaking to recruiters and try to match make the process basically. And so now people kind of send me jobs and say, Hey, I'm looking for this. Do you have anyone like that? And recently I had a guy reach out to me, a CEO of a company. I will not say which, but it's anyways, it's, it's a big business and they, but they've never actually had a data analyst or data scientist. So I guess not that big. I guess it's a midsize company, actually probably small compared to everything in the world. It probably has like. 100 employees. And he wanted to hire a data, data analyst or a data scientist. And he's like, I'm going to write the job description and let me know what you think. And he came back to me and it was this, it was a data analyst role, but like all the requirements were data scientists, like requirements. And I was like, bro, this is a data scientist job. And he's like, well, what's the difference? And so sometimes the people, you know, writing the job, hopefully this isn't always the case. Like, I don't know. I hope, I hope this is an exception, but like, he didn't even really know what he was talking about. And that's, that's why he was talking to me. But sometimes, sometimes, especially smaller companies, they don't know what they want, or they're listing like 100 things and they don't really need those things. They need, they need two out of the hundred things. So you never know, it can never hurt. But, but one of the things I think is, is most valuable that you did was you're, you're leaning on your networking, you're leaning on the people, you know, you know, you're, you're in the data career jumpstart discord, you're talking to DMing people, you know, who, who know me, like you're, you're leaning on the community around you and using the network that ended up landing you the, you know, the, the awesome job. And a lot of the times I think, you know, applying online does work, but if you can figure out how to like, Talk to a human instead of having to go through the system. I would always choose talking to human 10 times. Absolutely. Absolutely. I 100 percent agree every job I've ever had, and I've had six or seven jobs or because I knew someone that was working there already every single job. So networking is another undervalued skill. I mean, I don't, I don't want to say it's undervalued, but people don't practice it the way that you should. It was making those connections and building your skills based on those connections is just, I don't know. I would, yeah, undervalued I think especially on LinkedIn because like, I don't know about you, but like I do not necessarily enjoy networking events. Like where, well, okay I take it back, but like for instance, like socials, like where you like just have to like go up to someone and introduce yourself. I'm not very good at that as an introvert, and I know maybe you guys don't believe me, but I'm super introverted and like I'd much rather have like a topic, so like for instance, if they posted on LinkedIn. I would love to comment on their post, or, or maybe they'll come on my post if I post like I like having like a vehicle, where our conversation flows versus just like meeting in person and, and also like on the internet. I can tell, I know exactly who you are, off of your LinkedIn profile. If we go to a real life like mixer. I'm just like judging your appearance to like, hopefully know what you do. And like, I know that I went to the Silicon slopes conference, which is like a pretty big tech tech conference in Utah. And like, I was like, how do I maximize my time? I'm going to like meet some random people and like, you just walk into people and be like, Hey, what do you do? And it's like, Oh, like I make potato. Like machines, and it's like, okay, I'm sorry. I'm not really interested in that. And I can't relate versus on LinkedIn. I can be like, oh, this person, you know, works for a marketing analytics company. That's super interesting. Let's start a conversation there. So I just feel like I feel like LinkedIn is still underrated for the networking aspect of it. I don't know. Yeah, I think events like that, they kind of force this genuine connection when you can't really force something like that. Especially at those events, you're, you're expected to ask people what they do. You're expected to be asked what you do. Whereas in LinkedIn, you can choose that. You can choose to let anyone know as much as you want to, but also, you know, you have your profile and all that stuff. But yeah, it's just, it just lacks that genuineness. Yeah. And who knows, maybe, maybe, maybe I do like in person events. So maybe Maybe I was just that too broad of an event and maybe like, like, for instance, I have enjoyed the data conferences that I've gone to. So maybe it was just too broad but anyways I like LinkedIn because it can be really like I'm much better on one on one versus in group so big big fan of LinkedIn. Okay, so, With that, I'm just going to rehash your story. You're working for this mortgage company as a tech support, graduating college, join, join DCJ, start posting on LinkedIn. You know, you're by the way, your LinkedIn profile looks really good. I love, love your cover photo. That's one of the things that we go over in DCJ and no one uses the cover photo. In a good way. A lot of people don't anyways. So love it. Love your profile picture. Great, great headline on your LinkedIn. Posting good things. You're using the featured section, which is another thing. Your first thing is your portfolio. Next few things are cool graphs and viral posts. So you're nailing, you're nailing the LinkedIn thing. Land a job through networking, you know, 15k increase. In, in salary, you know, you're working remotely, which is awesome, enjoying life, have room to grow. So that's, that's kind of the Steven story that we want to shout from the rooftop rooftops and let everyone know that you can, you know, you can go from, from, I don't want to say nothing because you are definitely something, but, but non non data jobs, non data jobs to a data analyst role or associate data analytics role in three months. Yeah, absolutely. Crazy journey I've been on and still going on. So I just want to give you all the biggest props because there's people inside of data career jumpstart. Who have been in there, you know, like how long has it, I guess we started in September, September, October, November, I guess like eight months who are still struggling. And one thing I think you did really well is one, you took the content really quickly. You built and like fell in love with your portfolio like you're like my portfolios is where I post stuff you documented stuff really well. And then you networked. I mean, those are really like, honestly, that's what data career jumpstart is. is all about. It's like those three things. It's like, can you work fast? Can you make projects? And can you network? And you did those three things well. I think that's why it led to, you know, your success so quickly. You know, I think, I think at the end of the day, that's, that's pretty much, you know, how you got to where you're at. And now, now you're helping other people. Now you're learning more. I know you've, you've been mentioning, you've been SQL on the job and, and that's the whole point, right? Yeah. Like, I think I told you this straight up, because we had a call before you joined Data Career Jumpstart. I said, I don't really want to take you from being nothing to the best data scientists on planet earth. I want to help you get your first job, get your foot in the door, so you can get paid to learn. Absolutely. And that's what you're going to do now, right? And hopefully, I mean, tell, tell the people what you're, what you're learning and then what your, what your goals are. So yeah, definitely. I, During the interview process itself, it was actually very conversational. We never talked about anything that I wasn't, I never had to say too many times. It was very good. I loved talking to, I had basically, so I had three interviews back to back to back from I think nine o'clock to twelve o'clock. In the morning, but it was I wasn't sweating. It was like the most genuine So I got to interview with my director who I currently direct our report to right now a senior manager and then another a senior Director too, which who all work on my current team and they were they're absolutely amazing people and I love them And one thing I want to shout out about my director and why I love So I've only been working there for a little over two months. And we have flexible time off, so FTO. And she's like, Stephen, you've been working here for two months, you haven't taken time off. You should take some time off. I've never worked for a company that told me, Hey, you need to just, you know, you might burn out. Just Take a break, take it off. And I was like, okay, that's cool. But yeah, anyway, that's awesome. Yeah, it's, it's been an absolute journey. So they, they have been teaching me a lot of things. So that was one thing that they made sure of in the interview process. Have you been exposed to SQL? Have you been exposed to Tableau? Have you been exposed to Python? So I only had one technical question during that whole interview, which was, so here's a table and then she described the columns and here's another table. She asked her, how would you join these or what join would you use? And I was. Able to, I actually had a, a definition of all the joins, cause I, I kinda knew that they might ask some join questions on one of my screens. I have three screens, basically. So I had, on one of my screens, I had, I had, oh, what a full join was. I was like, oh, full join sounds like something I would want to use. She was like, yeah, that's, that's what you would use. And I was like, cool, that's about all I know. About SQL besides, you know, the main definitions select from where group by all that kind of stuff, but yeah, they're basically giving me SQL lessons right now. And I've just been learning, I know Python. It's just learning pandas, sqlearn, sklearn a little bit more and stuff like that. So it's definitely the ideal situation of getting paid to learn and knowing from the get go, what the expectation was really made it easy for me to transition into it, and I'm really excited to learn more because one thing I want to talk about is like, So many people are asking me for advice. They're saying like, oh, you know, so much about data analytics. I'm, I'm literally the first rung on the ladder of data, but like the way I think about it is there's a, there's a big gap from the floor to the first rung to like, you know, the, the ladder of data. So people are asking me so many things and I, I'm trying my absolute best and I'm, I'm a people pleaser by, by nature. So I try to answer every DM, try to answer every comment and it's, it's starting to burn me out a little bit. So I'm not forcing myself too much, but it's just crazy to me that people are, Relying on me or like trusting me with helping them in their career when I'm literally just the first rung on that ladder. So it's been super humbling and it's been super great to help out the community any way that I can. Yeah, totally. Well, I think, I think in order to be like a teacher or like a mentor, you really only have to be one step ahead of the people. You know, that you're teaching. So I think, I think that's, that's totally fine. And, and at the end of the day, we're, we're all still learning. You never will know everything in data. So it all, it all works out in the end. And I think, I think people talking to you is a good thing for them, but I totally understand the burnout aspect. That's one of the reasons why, you know, before, before I did data career jumpstart, when I was still working my nine to five at Exxon, I did a lot of mentorship. I did a lot of live calls. I did a lot of DMing and it got to a point where I was like, okay, I'm at my absolute cap for what I can do, you know, at this point. And that's why, one of the reasons why I started Data Career Jumpstart. But awesome stuff. I'm stupid. I'm, I'm not stupid. I'm super stoked for you and your, your journey, the way I see you, like your next, your next, you know, couple of years, like, you know, you're going to nail a bunch of SQL right now. You're going to learn a bunch of SQL on the job. Get really good at SQL. Um, you know, do really learn the business. Cause I think marketing something that's new to you, it'd be new to me as well. Like really learn your domain. And then, you know, maybe, you know. I guess you started in February or, or March, you know, maybe six years down the road, or not six years, a year or two down the road. You know, maybe you, you switch to a different team, or, or maybe you go into like a, a data scientist role and you do that for two to three years and then, you know, all of a sudden you're, you're like an expert, you know, data guy in marketing. You combine those two things. That's a huge niche. I, I, I see such a bright future for you, man. I'm, I'm super excited for you and couldn't, couldn't be more. More happy for you also couldn't happen to a better person. So congratulations on all your success. You know, just, just to recap 15 K new job has way more, you know, place to expand 3000 followers on LinkedIn in like, in like four months, basically. That's crazy. And I think it goes a huge testament to who you are as a person. Right. Thank you so much, Avery. Yeah. I just, like I said, you're, you're one of my mentors in this data journey and you've been an absolute huge help in everything. So I love everything that DCJ has been able to let me do and grow. It's still, it's still helping me even after I finished, you know, most of those projects. So looking forward to that sequel part when that comes out. Oh, it's, it's coming out. It's coming out soon. So yeah, looking, looking forward to that as well. And yeah, great stuff. Any, any parting words you'd like to leave the people with? Yeah. So it's, it's going to be a tough road, but like, I. I don't want to say that because of my skills I got to where I am, but I, one thing that my brother, I've heard my brother say is that luck favors those who are prepared. So I, I want to say I'm very blessed and I'm very lucky to have meet the people that I have met and also to get to be in the position that I have, I am in, but the thing is you got to be prepared. You know, you got to put the work in, you got to study, you got to learn and like when luck, when luck happens to you, you're prepared. So that's just one thing I would say. For sure, for sure. I like that. Well, Steven, it's been an absolute pleasure. We'll have your link to your LinkedIn down below. And yeah, we'll see you more on LinkedIn. We look forward to more posts. I hope you enjoyed that episode. And if you did, I'm going to have an awesome free masterclass that I know you're going to love. We're going to talk about a lot of things this episode talked about. You can get it absolutely for free at data career jumpstart. com slash training, or using the link in the show notes down below. Hope to see you there.