839: Double Your Data Salary in 11 Months, with Jess Ramos
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This is up so number eight hundred and thirty nine with jess ramos, founder of big data energy analytics.

Welcome to the super data science podcast. The most listen to podcast in the data science industry. Each week, we bring you fun and inspiring people in ideas, expLoring the cutting edge of machine learning, AI and related technologies that are transforming our world for the Better.

I'm your host, john chone. Thanks for joining me today. And now let's make the complex, simple.

Well, go back to the super datis ze podcast today. We've got the charismatic, well spoken and super intelligence just ramos on the show. Jesses, founder of big data energy, a company that supports her in demand courses on sequel and data analytics.

She's also a senior data analyst at crunch base and previously worked as a senior risk analyst and a data analytics manager. 而 popular social media content on single data analytics， data science, tech advancements and maxims ing professional growth as a letter to amassing over three hundred thousand followers across ldn, instagram and tiktok. SHE holds a bachelor in math and SHE also holds a masters in business analytics from the university of georgia.

Today's epo de will appeal especially to folks who are looking to grow their career or grow into a career in data analytics or data science or a related field. In today's episode, Jesse details how SHE more than doubled her data analyst salary in less than a year. SHE also talks about the questionable value of data signs bt gams her controversial take on grow math that may display h in international mainstream news, the unexpected viral post that launched her into social media fame and essential advice for anyone starting their data career journey are, are you ready for this fun episode? Let's go.

Just welcome to the super data science podcast. It's awesome to have you on the show. Where are calling in from today?

I'm an at in storage a so it's like a small ish town about an hour from milena a product.

Probably a pretty exciting time to be a few days before the us election is interesting. When our listeners hear this, they will know the outcome that you .

and I don't yeah that's crazy like to see.

Um so let's dive rate into the episode content. You have a math and business and latics educational background, and you worked in both startups and more established organizations. Currently, your ninety five is as a senior data analyst crush base.

But outside of that, you've a massed a large following on social media, creating content about data science, data analytics, tech news and career development. And you have a unique and imaginative voice that obviously has been a hit because you've got a crazy number of followers. It's really wild.

I've got some of the numbers here at the time of recording over two hundred thousand followers on linked in ninety thousand on instagram, over twenty thousand on tiktok. It's pretty wild. So you you know you've carved into use for yourself.

It's obviously going very well. It's LED to brand partnership speaking collaborations. And last year you founded the amazingly named big data energy yes, I did um company and that supports all of these efforts. So what's the origin story of your career in data and this big data energy brand?

yeah. So at my origin story for my korean data, I was studying math in school. Math is something that just always came kind of easier, kind of natural for me.

I love to think through logic and number members, but I didn't know what I actually wanted to do with my math degree um so that LED me to pursue with my masters and business analytics. And lucky, I was also able to get in internship in undergrad and then again in cdd school. So that was able was able to test the waters in data and see if I actually you like the career or not.

Um so yet from there, that internship LED to a full time job. I moved up a few times to a senior data analyst, da analytic tics manager, and then i've switched jobs twice since then, not really set me up for a great career in data. And then my origin story for content I really just posted on lyndon when I like on my phone, I was like a sunday night at ten P.

M. Was like in bed, just like typed up this pose and I went like viral IT was about remote work. And I was like, what this is so unexpected, like, I wasn't trying to be a content creator.

I just found like an amazing community, kind of an accident and I was like, i'm a one who wonder no one is actually gna follow me. I was scared to post again and my coworkers were like, no, just like you, you're going to do fine. You'll be great and from there i'm just like, super blessed even hearing the numbers of with you introducing me.

I'm like I can't believe that many people follow me like I always think about IT in football stadiums. I'm like, right? That's like you know three or four stadiums of people and every time I go to like a big event like that, I look around i'm like this many people times three follow me on so I mean, is crazy, but i'm super just blessed have the opportunity to reach so many people and resonate with so many people as well yeah.

it's very cool. congrats. And so what was the second post about your member?

Um the second one was about secure. So I think IT was top ten optimization tips that I don't know was something to do with equal, which was very different from my first post. But that one got around a thousand likes and this was back in the linked in golden ages.

This was two and a half years ago. Like views were really good on linked in back then. But yeah, that posted well to and from there.

I kind of developed my knee over time. I've even changed you a little bit and reshaped IT know depending on what my career goals are. So it's been fun.

Well, that is exciting that your second biggest post ever was about sequel because you have a equal course coming out right now. It's coming out the day after this episode is out.

Tells about IT. Yeah, so I have had this dream of making my own equal course for a long time. I was really lucky to make two courses with linton learning.

One of them was in. And I just learned how to make a really good cores. And I got so much positive feedback from this cores.

So from there, IT was my dream to have my own course that has my name on IT. I have full control over, and I can do whatever I want with IT. So this is something i've been dreaming about for a long time, and that my course is called big equal energy.

So we're still sticking with the branding, big data, eric, big sick energy, keeping IT fine. Um this course is is an intermediate course. So I start off with joins and then kind of go up from there.

So I do expect that people have a little bit of basic equal knowledge coming in, but I really notice that there's not enough intermediate courses out there, and that's why I really wanted to fill in that gap in the market. There's so many basic equal courses out there where people just learn select start from table. They're doing just super basic things.

But they they finish these courses and they don't actually know how to use equal in the real world and how to use IT to solve business problems. So my course is actually taking those equal skills to the next level. And people are going to work through these business problems in these scenarios.

And I even have little like stake quarter scenario in there too, like so and so just knocked on your door is a last minute request. What are we going to do? So i'm really just trying to take that learn into a real world environment and to really think critically through more intermediate advanced concepts.

Sounds real variable and sounds like mechanics that I need to be taking with my relatively rid tim tary equal capabilities. Ah so where can this course be found? You say your names on IT, you so this is going to be available through the big data energy like website or something.

yeah. So ironically, I don't even have a website for my company. I just have a look. I just have a lingery, but i'm hosting IT through teaching.

Teaching has been an amazing partner for me, and you wouldn't even know that it's hosted on teachers because they do such an amazing job supporting course makers and creators. So it'll look like IT really is my website. So i'm able to plug in, in all my stuff there and someone is able to access the course through their portal and their platform. And I can give you a link to for the shown note, if anyone is interested.

fantastic. That would be great. But IT sounds like IT IT will be easy for people to find you on, social media, to find you on like in or instagram or wherever they prefer to get their social media content and then they'll be able to find your course through there because that's presumably something you're going to be talking about a lot over the next few months.

totally. It'll be in my links tree all over social media. I promise you can not miss my course launch.

I will find you nice. yeah. So equal obviously is important in a data science career for our listeners who may be aren't already a da analyst or da scientists. Can you explain why equal is so critical?

Yeah so sequel is in older coating language to spend out a long time, but is something that is just the backbone of data. IT is the bread and butter of really any type of data role, and it's something that companies have depended on for a long time and will continue to depend on for a long time. So it's a very established skill set that companies are already using, and it's really not going to go anywhere.

So equal, if you're not familiar in your listening, seko is a language to query a data base. So it's basically the language you use to pull data, make data, says, reshape IT, do data cleaning everything you need to do to get data out of the database and get IT ready for analysis. So you can do analysis inside of equal itself, or you can even pull the data into a business intelligence tool and do further analysis there. So IT was a really important skill that you're going to use at least some point in your career no matter what type of data role you're working in.

And the most popular language in data science or data analytics. There's often this kind of although happens, listen less. But there was a time where there is this kind of python versus r debate. Now it's kind of mostly settled.

It's kind of settled.

Yeah but during that whole era, he was kind of amusing to neck because it's like, what is the language data science? It's not python or r is equal.

That's so true exactly. People ask all the time they're like, should I be learning python if I want to be a data analyst? And yes and no, python, of course, is a very like visual programing language. You can do way more n in python, but if you're going for an entry level role or maybe a company that isn't like, as you know, modern with their technology, you might not even use python on the job. So sequel is like the bread and butter .

for sure um so all right so that gives us your kind of equal take.

which I love equal if you can tell .

yeah and there are already as you said, um there is also course is on linked in learning that you created later to equal l people can check those out as well in addition to the new course. Big equal energy officer, I love that name. I so we have your insights now just into why equal is so important.

And we've got your course again. Then there is big equal energy coming out tomorrow, which can check out rate more broadly in planning or career, in data analytics or data science. You may to splash recently, uh, in in social media through doubling your salary in eleven months. You want to fill this in on how to listen, can do that themselves.

absolutely. And we gotta get the fact rate I over doubled IT and in eleven month time period. But who's counting just getting? yeah. So I did have any eleven month time period right before I started my rock crunch base about two years ago, where I did over double my salary.

And to kind of walk you through all the steps, I was currently working as a senior data analyst at a smaller phin tech. And then from there I negotiated an internal race. So I basically went to my manager in hr, and I was like.

I have a direct report. I'm doing all of this work. I'm leading all of these projects. I'm supporting the data for our capital rays.

And I making seventy, seventy two thousand dollars a year like I should probably be making a little bit more money for all the responsibility, ie. S i'm having. So I really built up that case of all of my accomplishments and responsibility ties. I analyzed the market data, and I showed that senior analysts, we're making about six figures.

So I went back to them with all of that research and advocated for myself, and I was able to increase my salary to ninety five thousand, which at the time, I mean, in over thirty percent race from an internal negotiation, I was stopped like, I am so proud of past just for doing that. And then from there I knew I needed to go somewhere else to continue burning. I wasn't really growing in my role anymore.

And this is like six months later or so. So from there I was on the job market. I just held my cars really close to my chest.

I did not say any numbers in interviews. You will not get a number out of me ever in an interview. So that's that's a .

key negotiation tactic in anything with you're negotiating your salary or any kind of deal where money is involved. That is like it's like negotiations one to one. It's probably a lot of our listeners are already aware of this, but you should never give know your number like what is know what's your salary expectation? I kind of think of what can salary are you on? Sorry, I can interact to do just but .

no you you're good and I ve heard to whoever speaks first loses that's what i've always heard about negotiation and it's really easy to be nervous in interview and just blurt something out. But I think just recognizing this is a very uncomfortable conversation is the worst part of any interview and just sit in that uncomfortable ess and just be OK with IT being kind of awkward and like, you know dodging the question, like but that's what you really have to do to get those increases and make sure you advocate for yourself.

Because when I first entered the job market again with my ninety five thousand salary, I was getting interviews for roles ranging from you know one hundred k all the way up to like one thirty five, one forty. And i'm like i'm getting interviews for these roles. I would have been excited to even just get one ten, one twenty, which was a big increase from where I was, but I just catch my lips tight, didn't say any numbers. I let them give me their budget and put the question back on them every time. And at the end, I negotiated an offer up to one fifty which I declined to go to friday mac for less money and then you know I I quit in for a months IT was not a great place for me to work, terrible fit but um I did end up getting an offer for one fifty which was well above where I was a few months prior and then from there, leaving friday mackoff ter for a months, I came to crunch base making over one fifty. And i'm going to be vague about my current salary only because I don't want to ruin my future and negotiations.

sure. And I actually really appreciate you being so canada about the numbers on air. I mean, it's great that you are keeping having the current one closed your chest, but you know to be able to go into concrete numbers like that know kind of openness that you really here people do on here.

And so thanks very much. Just um what do you think the impact of the early in ships? You've mentioned those when we kind of talk about your career background right at the outside of the episode, what do you think the impact of the early internships was on shaping your skills and the opportunities that .

you had subsequently? Oh, the impact was gormless. I think IT absolutely shaped my skills. I think IT shape my skills. But I think almost more than that, that shaped my interest, which is so important while you're in school and you're not really share what you want to do.

So when I was studying math and undergrad, I was like, how am I gone to apply this to the real world? And I kind of stumbled upon like a pretty casual summer data in a lights type of internship. And I was basically developing insights from enrollment data to kind of show who is in rolling in the school, who do we think, you know, my enroll.

And I was doing a little bit of like predictive work. IT was very like novice level work. So is that the work I most proud of at this point? no.

But IT was a great learning opportunity for me to learn an and a little bit machine learning and predictive analytics. So that's what I used to talk about in my grade school interviews because that internship taught me enough to wearing new. I'd liked working with data, and that's why I applied to grad school.

And then also able to talk about that internship in grad school, which was super important because a lot of people in my grab program already had full time experience. And I was a little baby underground. I didn't have any like real full time experience yet, but I was at least able to show that know a math major.

I've had this internship and I got me in a grad school. And then in grad school I got a local um dit analytics internship, which was like just a huge growth opportunity for me. I was using secure in a real database power by leading meetings with the sales team, providing updates in front of the whole company. So IT just was like the biggest learning platform I ever could .

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Follow data citizens dialogues on apple, spotify, youtube or wherever you get your podcasts. Mazing, that was really great. A another thing, in addition to internships that people often find helpful in their career is mentorship or manager erik support. In what ways as manager erik support a mentorship influenced to your career development? And I guess kind of more generally, we could maybe extra from that what you think the great qualities are in a data manager?

yeah. I mean, i've had so many amazing mentors just in the past and even now to but my first manager at this first shop is probably the best manager i've ever had from a lad to say that. But he was just so supportive of me, not as not only as a data analyst, but also as a person.

He genuinely cared about me as a person. He gave me the time and space to work through problems, even though I was brand new and those problems were very difficult at the time. He gave me that space to figure out of my own and then come back with questions.

He never made me feel stupid if I made a mistake or didn't know how to do something. So I think he was a really good baLance of giving me the time and space to go stubborn, like figured out on my own. But then he was also there.

You helped ed me out when I needed IT. And then, of course, he gave me so many growth opportunities like leading these sales calls. I was leading, doing our company wide updates. I mean, he really grew me into that senior analyst. And then when he moved to kind of a different department a little bit, I was able to step up and be a manager and hire two people under me, which was great. It's an ideal scenario for a manager.

Very cool. I mean, that sounds like IT was all positives. Are you able to see this person's .

name in the company? Yeah um so the company was formed free. His name is Caleb. We treat I I I just said his nate last name wrong and it's just a really hard last name to say. So he's going to listen to this and be like just do us and know how to say my last name and then he also recently got married to so he might have um I know he was thinking about changing as a name .

so he might not even exist that name anywhere I think then but thanks kill up sounds like a great manager and we at least have know some information on that great positive influence as a manager er in your career beyond the the jobs that you've had your increasingly entrepreneur. So when was the moment that you decided you know what I need to start big dat energy, I need to start this company. Um you know what was the event that allows you to go from being you know in the U S B C just like A W two employee where you're just you're earning a salary income and go out and and do your own thing?

Well, to be quite blind, I started making money through just different brand deals, my linton learning courses, and I realized I was bringing an income outside of my regular jobs. So i'm like, shoot, I need to go find an account like I know one of to pay taxes all of this later. Like I need to get my ducks in a row and I just didn't know anything about IT.

So going to my account, he was super helpful for me to like, know what I needed to do, you know, save enough for taxes later on and get things kind of square away. So from there I developed the L. C.

And then then q four of last year, twenty and twenty three was kind of like a very growth year for me. I was making, like my first dollars in my business, working with all these amazing companies and brands. But IT wasn't until you for that.

I really exploded for me. I was getting noticed by companies like S A P. They flew me out to new york to come to a super like tightened event with like their top leaders, top partners, because they wanted media coverage for IT.

And they knew I was the person to help with that. I got asked to go to IBM think in may, IBM flew me out to boston to report on their event and create. Instagram reals for them.

So like seeing these big companies notice me is like is still shocks me every time that they even want to work with me. But it's an amazing opportunity for me to you know share cool things with my audience and also be a partner to these really cool brand that i've looked up to for a long time. So really twenty twenty four was kind of my year of like I am actually like making IT on my own, like my business is sustaining itself.

I've hired in intern a video editor. I have like adult big girl expenses here. And i'm like, how am I doing all of this? I have no idea.

A congress just that is great. IT sounds like clearly developing your audience, developing your social media following was part of the key to, you know, those examples that you give. I B, M flying you out, asking you to create instagram reals and give exposure to their events.

And so would you recommend to data professionals? Data analysis, a scientist? S may be off for developers, our listeners in general, who should be creating social media content. Should everyone be what value does create in their yeah I mean.

in an at minimum, I think everybody should be active, at least on linked down. I know not everybody is comfortable being on camera. Making instagram reals is a very like vulnerable and humbling experience, especially when you for a start um but I think that minimum everybody should be on linked down.

There are so many professionals out there that want to connect with you that you can learn from, that you can teach good job opportunities from. So being active on lington, making at least a little bit of content and engaging with other people in doing coffee chats, that is gonna be just so good for your career long term. And it's just a good way to network.

I can get your name out there any time I go to a city. I'm like, I know so and so there maybe we can meet up any time i've ever needed career bias or i've been looking for a job. I've had at least a list of people that I knew I could reach out to for guidance or a potential job opportunity.

So building those connections on lindon, I think, is like the minimum for like a good strong network for your career. But I would would encourage anyone who's interested to take a step further and post on other social media platforms and be more of a content creator because there's so much opportunity to to start a sid gig from that and there's actually like real money with working on social media like that sounds silly, just making these little videos. It's even crunchy sometimes, especially five to like film in public, but it's an actual career in business that you can do on top of your nine to five at whatever involvement level you want to and actually have real side .

and come from IT. Nice a great summary there. Let's move now onto some of the work that has come out of all that social media work you've done the past. Um does make a lot of sense to me, obvious. Ly, you're pushing to the quire bit with me about creating content.

Uh, obviously I do think that is also useful um but in terms of york reer, obviously things like uh not just going to IBM think in doing instagram reals, but also things like having a serious linked in learning course. Now your own course, your own brand teachable course on bixio energy. Um I not not on, but I guess that's the name of IT.

I probably people understood what I said even if IT wasn't the best grammatically uh order sentence. The point is that your social media presence has LED to these serious opportunities, including more than fifty thousand people taking your linked in learning course on equal um so yeah so it's clear that you have this uh disability this a talent at translating complex data problems into teaching content that resonates with professionals at a wide range of skill levels. Um so it's it's kind of this there's an interesting journey there that I wants to dig into a bit.

So it's you know creating social media content, which obviously you know you been able to create stuff that really resonates with people. And then when you have the opportunity to be to be creating course where you were similarly able to yeah connect with people to, as I, as I just had, translate complex data problems into teaching content that resonate with people that makes sense to people. Do you think that there's anything that you can tell us about that skills? Said um so that you know we can become Better at IT ourselves. And because IT sounds like you know this kind of ability, it's not it's not just useful when you're making courseware or when you're making instagram. Reals is useful in everyone's workplace.

Yeah, totally. And I think for me, I don't take anything too seriously. I mean, I do, but I don't at the same time, i'm very serious about my work, especially when I get to work mode. But I don't take things too seriously all the time like I like to have fun. I never wanna game, keep information and like you know, make things super smart and technical and confuse people so they feel badly about themselves and see how smart like i'm not that kind of person.

So when i'm explaining things on social media or in my courses, i'm speaking to people like their real people like I make these videos like i'm just talking to a friend and I even use silly metaphors. So for example, in my course, when I teach unions and equal, I talk about making a sandwich. You're building all of these pieces and stacking them like to use those fun metaphors to make things easy to understand for anybody. So my biggest advice to grow that skills sit would be to take on the technical jargon and just pretend like you're explaining to .

a friend nice that is great, actionable inside. I thought I might be a tRicky question, but you nail that. And so obviously, being able to communicate complex problems to people in the kind of relationship whether you're describing is key to people's career success. When people are starting in a new career like data analytics or could be data science, we've obviously talked about sequel being an important skills.

Do you think that's the first skill the people should be learning or amongst the first skills, I guess, kind of in kind of broadening from just equal, you know what are the other things that people should be learning for us? What should people be prioritizing? And yeah is equal like the first thing or one of the first things amongst that said.

So if you're like brian noted data like you truly don't have any foundation at all, I would say definitely start with like a little bit of data visualization, maybe play around empower bi or tablet or even excel and just understand some very basic, so like columns and rose, different data types, how you can visualize data differently, maybe like bar chart, flying graphs, a little bit of basic statistics, like maxim average, things like that.

So you like brand new I D definitely start there. But I actually tell people they should really start in sequel as long as you have a little bit of a data foundation, because I think equal just brought in your data experience so well, you start to learn how data that emerge together. You get to learn a lot about data cleaning and how to reshape and transform data.

So I think once you learn those skills, you can easily pick up anything else. So if you already know how to do IT well, in simple, you can go into power bi or tablo, or whatever bi told you want to use, and apply those same concepts and transfer that knowledge over. So I do think equal is probably one of the best investments because that's a skill that all companies are gonna like regardless of where you work. And then IT also gives you good knowledge that you can transfer over to whichever bi tool your companies work again and then also python or are later down the road too nice.

Um so a lot of people, when they are starting in their careers, they would be thinking about educational programs that they could follow. So you know you just give a great list there of the kinds of skills that people would want to be learning. But a lot of people they want to learn amongst other people are along side.

Other people can uh you know having a teacher uh giving them uh, guidance and mentorship as we talked to Better early in the sub of the importance of mentorship. So there are lots of online courses and bo camps out there on data analytics, business analytics, data science. You yourself have gone along, but I guess we could call the more traditional route of getting an undergraduate degree in math and then a graduate degree in business analytics.

So what do you think about those two different kinds of paths of I mean, I actually I guess there's three there's three to consider because there's so there's what you were just talking about in your last answer is actually something that somebody could do completely unstructured, uh, where you're just you know you're chatting with something like ChatGPT even you know just kind of your own guided self of education. Um one step more formal could be doing a boot camp or on a collection of online courses that you create for yourself. And then the most formal would be to get degrees to go to a university and to get a formal education, formal diploma, showing that you have, say, an analytic skill set or a machine learning or day science skill set. So what do you think about those various routes? And what would you recommend to different types of listeners?

Yeah, so I think the choice really does come down to the individual is cheesy as that sounds. But I think everyone has different goals. Everyone has different financial means and different time restrictions.

You know if someone has a full time job, they might not have as much flexibility with certain options. But I would say that i'm glad I went to grad school for me. I was a personal goal to go to grad school.

I actually dreamed of that as a kid, like I was like, i'm gna get a PHD masters degree when I grow up. So for me, IT was very much like an educational goal that I had, and IT was obviously a very structured way of learning da analytics. And by the time I graduated, I had all the skills I needed to go and apply for jobs, plus the added credibility of having a an extra degree.

So I think that was a huge pass. But I know realistically, financially, not everybody is going to be able to go to grad school and a lot of people aren't going to be able to pause their life for a year to do a full time grad program. So by no means am I saying that everybody should go to grad school.

Um I think when IT comes down to learning on your own, I think the two kind of routes are a structured way, like a boot camp orders, kind of like. Yourself learning path where you can pick your own courses and stuff. I think if you have the discipline in the motivation, absolutely like curate your own learning path, like learn other right skills, take like a few courses, maybe spend like a few hundred box on a few different courses that you know, we're going be really good and set you up.

And that is totally enough to get a job in data. But IT, of course, takes a lot of discipline, a lot of time. You've to build projects on your own and really practice and get those skills up to here so you can pass your interviews because you're knocking to have the same credibility as putting a masters on your resume.

But you're going to save a lot of money and probably a lot of time too. I think the bo can't path IT depends on the boot camp. I do not like seeing some boot camps charging ten thousand dollars, twenty thousand dollars. I mean, my grad program was twenty thousand dollars.

So i'm like if you're going to spend ten or twenty thousand or take out loans, you might as well just get a masters because if you're going to make that kind of financial investment, you should at least get a diploma for your wall and put some letters on your resume, you know. So i'm not a huge fan of predatory bo camps that are very expensive for for what they offer, but I do also think that there are very good boot camps out there. So shot out to sak Wilson, his state engineering boot camp, like he's obviously very credible. His Prices are very affordable like that, something that I would buy into versus one of these big corporations that kind of praying on newbies.

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Some more real talk from you in this episode. I appreciate your openness and you yeah telling IT like you see IT uh you know like really in the episode going and to specific numbers on your salary now talking about you know these specific numbers and value that you get on on boot camps. And I totally agree with you, there are definitely predatory kind of Prices out there. Um well, yeah, you could be getting a lot Better value on either of the past that you described getting that graduate degree for the ten or twenty thousand dollars or creating your own path.

And as you said, you know that requires some more um some more motivation, although IT just a good to me off the top my head that potentially away that you could very inexpensively if you if you can somehow find even just a handful of other people that are also interested in developing a career in data analytics, data science, machine learning, they could be people who you met all mine. You could literally post about IT on link in and say, hey, i'm thinking about going into career in data analytics. I come from this background, you know here's some the resources I was taking maybe learning or lets together come up with a with a course plan and all the other accountable.

You could like you said, for hundreds of dollars, you could um you could develop all the same kinds of skills in a ten or twenty thousand dollars O K. Camper, even a ten or twenty thousand dollars masters potentially. And that independence showing that independence, you're going to be developing a lot of skills there yourself that are either employable skills showing that, you know, you are able to figure team or to organize a group or independently as an individual, be able to curate the rate resources to succeed.

I mean, that is a highly employable skill simultaneously. Those are the same kinds of skills that allow you to be a great entrepreneur and to be making money on your own. So so I know so a number of different ideas there for people to think their teeth too.

Yeah, I hope I didn't talk too badly about good camps.

I mean, this I mean, and you know there's also there is probably also um you know well, I would think carefully about IT. They're probably also our scenario where you think, okay, you know what um I have this career AK right now. I've got three months or six months because i'm ungarnished from uh you know I was I was working in a big bank and they've given me gardening ly for six months um money.

He is not a problem for this person because they have just like left an investment banker, whatever they left to sort develop a job and investment bank and they are like, I want to be A D A science st. I want to get in the machine learning and you know you don't want to take that year or two years to get a masters, especially if you know you'd be pursuing a part time you think, okay well this book camp um you know even those a bit more expensive. I can get immersed in this rate away. And often with that kind of praise there, they do put a lot of effort into uh, partnerships with industry, which is something that you that is kind of a big part of, I think we are buying with that Price tag.

Yeah, I agree. I think the right boot camp can be really good for somebody, especially because some people do want that structure. They won't be told exactly what to learn, how to learn IT and when to learn IT.

So I think that's great along with the industry connections. But I think once you get into like the ten thousand, twenty thousand dollar range, that's when i'm a little like is IT really that much value? I don't know if that just might take. I wouldn't spend that much unless IT we're for a masters.

We've talked a lot about generally what people can be doing to further the themselves in a data career um something that we haven't talked about that you advocate for a lot is stereotypes in the data industry, the tech industry more broadly, uh particularly uh for women you've been advocating. So uh you've demonstrated that women can thrive while staying true to their confidence cells in a data career. And you had a viral tiktok video last year which was featured by uh mainstream news organizations like the BBC and uh that that viral tiktok highlighted the problematic nature of something of the girl math trend, which actually isn't something I am aware so can explain that not just the our listeners but literally to me uh but that you know you you highlighted in this viral post how uh grow math perpetuates negative stey types.

Do not tell us about that. Yeah so mean, you're really put out the receipts for this podcast episodes.

our researcher and he's unreal. I am so grateful to him and I hope listens to the episodes. Also, let me say, like every second, third episode, I like, yeah, you know, guess like you are like, wow, again for you.

I forgot I did that. Yeah the first explained girl math to you and for anyone who doesn't know what that is. So IT was a very like silly tiktok trend and a kind of spoke to the way that women kind of think through like shopping.

So an example is like I just bought the shirt from the store with thirty dollars. Now i'm going to go return IT. So now thirty dollars, Richard, is girl math. But obviously you're not thirty dollars, Richard.

You're just getting money back that you are spent or maybe you have a you know twenty percent of cuban for something so you can go spend that money that you have saved on something else like it's basically empowering you to do something else with your money. But IT doesn't exactly like add up. So it's kind of poking fun at the way that sometimes girls think through shopping and money in that way.

So there's all these videos out there about girl math. And yes, I do see the humor in IT, and I do think it's funny. I laugh at them because I think the exact same way I think about money I spend that way as a joke.

But I think the way that some of the girls were making videos on IT, I think I just kind of made girls like silly, financially irresponsible. And there's certainly two sides. This argument like when I first posted my video about how IT makes girls look financially irresponsible, IT makes us look um like we're not able to handle money and perpetuate that stereos type.

A lot of women came in my comments and we like, no, this is building community. This is girlhood. So I totally see that side too, because us girls, we have to stand together and have that community.

But I also got a math degree. So, you know, sitting here as someone who went through this math program, I didn't get fully respected by the other students or my professors. I am a very outspoken and girl girl.

And I got the point to where I would plan my outfits around my four hundred level math glasses if I had a really smart math class. You bet I wasn't onna come in wearing my heel boots in my make up and no, I would change the way that I looked because I wanted to be a respected for. And like thinking back to that, you're probably like just did that like there's no way just as unapologetically herself.

But I wasn't back then. I had to fit the mold of what I was like to be smart and be a math major. And then, of course, there's all this subjective grading in the math department.

And you know, i'm not onna say that things happened because I was a woman or because the way that I looked to, the way that I acted. But I think women have to fight twice as hard to get that respect. Women have to prove themselves where as a lot of times, men already have that respect in confidence coming into IT.

And then on top of that, women are more likely to understand themselves and not advocate for themselves, which just, you know, kind of snowballs. And seeing that in my career and also as a math major and undergrad, seeing girls, can I have like chills talking about this right now, but seeing girls like talk about like girl math, we're so silly, we can't manage money. We're spending thousands of dollars on crothers, which no hate.

I also spend a ton of money on shopping and cloth and pink stuff and designer purses, so no hate at all. But seeing IT kind of poked fun at and then seeing all the men and the comments being like, this is why I control my wife spending. This is why I control the money in my household.

I was just seeing a lot of like that kind of backlash from that trend, which kind of like broke my heart away. So I made that video. I just hold on.

Tiktok posted IT film when environment, tiktok and instagram, because obviously was a controversial take on the subject, and I actually had girls turned against me for that. I was like, what are all doing to help women in stem and help these stereotypes? I have a math degree and i'm study and i'm working in data analytics. You like, I feel like that's doing more to help the stereotypes, then making little tiktok video is poking for at them. That was a really long rat pot.

I was an outstanding ranch. I don't I don't feel like I have like this is something that I don't know like it's kind of like I don't feel super comfortable, you know waiting in on like I do about who camps. It's like, you know but I I loved everything that you said.

I was like you talked about having chills me too. I mean, that was the way that you delivered that the argument was super compelling to me. And IT seems really obvious and IT seems like there is a huge amount of opportunity still know we we I think in many ways in society, we have come a long way on bias against lots of such demographic groups, including women.

But we are still there's still so much further to go than we've come is of I guess I now I am kind of giving an opinion anyway, but that of that that what I see when you tell stories like that like dressing differently for four hundred little math class and other classes that you're taking, I have never thought of anything like that in and a yeah I guess it's like I said, I enjoy like the privilege of not having to think of that and I my whole life and so yeah so thank you for everything that you just said on this topic. And I really appreciate the work that you're doing and the message that you telling. And I really resonated with me.

So thank you. And I hope that you know IT nudge my thoughts and my behaviors to thank you know, uh, when i'm when i'm speak to a woman in the workplace round, detect topic or math topic to try to be. More mindful about the perspective that you just released and may be that'll have some some impact on the way that I convey things or what I can be um that it's you more supportive um and yeah more thought ful appreciative yeah I think .

you know like what you said, there's there's so much progress that has been made, but I think there is a way to go to and I think it's the subbed thing. So for example, maybe a guy finishes a presentation and people are like that. I was an excEllent presentation.

I really love what you ve said about xyz a grow as a presentation. And it's like, oh, I love your outfit. You look so cute. You were so well spoken, you know, like, I think sometimes the way that men and women get different types of compliments, or maybe the woman is asked to plan the office piece of a party or is asked to be the note taker, the presentation making, do the admin kind of, you know, homemaking activities like there's these very subtle microage gressier that happens sometimes in the workplace. So yes, I think we've come a long way, but I always like to respectfully call that stuff out and speak on IT, because yeah, IT does IT just kind of hurt women's feeling. Sometimes we're not seen as as capable, even if the intention isn't to be rude or .

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I just well, thank you for obviously this valuable conversation that we just had around yeah gender in stem and in deter als and thanks for this whole episode. I ve learned a ton from you and have really enjoyed a being a on air recording with you. You have great data.

Energy is is so big. A um but yeah, before I let my guess go, I always asked for a book recommendation. You have anything for us?

absolutely. I should do so. One of my favorite books ever written is weapons of math destruction is a very popular book in the data world, but that is a book that I read when I first started learning about data.

And it's a book that I wish I could like reread again for the first time, because it's just so good. So it's written by cathal neel and SHE is a female mathematician, which of course, I look up to her so much and think she's amazing. IT talks about algorithms and how data can actually be used in an unethical way, even if that's not the intention.

So it's really pulling into like the soft skills and ethics side of data, which I love. And the book is not a technical book at all. There are no equations, no like numbers.

So it's a pretty easy and light read. It's not like you're reading a bunch of code anything, and it's truly something that anybody can enjoy regardless of their background and their technical abilities. So especially if you're new in data, it'll completely open your mind to how data can be manipulated to tell a story or even use in a bad way towards society. So is safely a super interesting book and you will totally change her perspective of data and a lot of societal things that we do. Awesome.

great recommendation. And I also just took a no down while you're speaking that i've got ta ask cafe on new to be on the show. I haven't had a .

on do you know her?

I don't know her.

Do you OK? No, I was like, why are you friends with her?

No, I mean, but yeah, one of the other great privileges I enjoy in my life is that by hosting, but we're pretty sure is the world's must listen two days science spot gas. You can just kind of cold reach out to people and you know, not everyone says he isn't not even response, but caffeine will be an amazing guest without ve air.

Oh, i'd for sure listen to that one.

Nice, alright, great recommendation. You got my the girls flowing, girls flowing gears, moving in my head, my tears are flowing, i'm in trouble. I've melted. Um um and very last question before.

What kind of done here is if you could kind of real offer us the most important places that we can be following you? We that we've got your course big evil energy coming out tomorrow. So probably when most people listen to this, IT is already out a linked in, we know is probably your primary social medium. You've also got your instagram account, you got your tiktok, both of which are super popular anywhere else that we should be following you.

yeah. So I also have my news letter. I have about fifteen thousand subscribers. It's called the big data energy newsletter.

Of course, you can also find those links on my other social media, but I send IT out. I mean, it's supposed to be weekly, but I honestly get busy. So it's like maybe three times a months on average.

But I sent out like data tips. I talk about salary negotiation skills. I talk about all sorts of things, data and take career.

And I promise I don't send any like spam or annoying things. It's all you know just extended longer form content like the stuff I write about a linked in. So definitely follow me there.

I also post like any big announcements through there like my course lange, and i'll probably be pushing some discounts and promos for my course to and there. So definitely stay there if you want to go there, if you want to stay up to date with that kind of self to. And then I also on youtube, I only have a couple of long form videos up as of right now, but doesn't area I wanna grow into so much in twenty twenty five. So if you want to be one of my first subscribers there subscribes to me like my video and give me some comments to help me get started.

nice. I look forward to seeing how that youtube develops them. sure. You're going to overtake my youtube numbers in like a months. You're really talented at this stuff.

It's like i'm going to i've been taking notes of this episode and i'm going to be taking more notes after read as well. It's really amazing. What if you're doing just great work?

I mean, we'll see if I get all my camera equipment set up for youtube that's been the biggest barrier, but we'll see.

Um yeah and so actually just had them just for me. Why do we tell him quickly of these tips you had you're telling me about this camera before we started recording, which i'm going to buy to up my so I, so for me, the long format stuff, obviously, these long podcast episodes, long youtube videos, that's been my bread and button for years. I have been terrible at like, you know I don't make or even view shorts or reals on instagram or youtube.

Oh well actually we do make we do pay people to make youtube shorts at least. Ah and I try i've tried to have a tiktok canal but like nobody nobody follows me on tiktok it's really embarrassing. Um but this kind of thing that you recommend you specifically IT, was this I put in the shown ots from a company, D, J, I, which is famous for like big.

When you have like big movie cameras, D, G, I makes the thing called the gambles that you can be moving around with IT and the camera stay steady. And so you told me about this osmotic pocket three. O S M O. Pocket three is a modal pocket cameras, just a couple hundred box, and you can run around and get great quality, uh, video, anywhere you are.

Yeah, it's great. I have had this camera for maybe almost a year, but I love IT because the quality is insane. It's a super small camera.

It's like for people not watching the video right now, the cameras maybe the size of like an egg with like a stick on IT, you know if it's in a purse easily. So it's really great for travelling, but the quality is amazing even though it's so small. IT films in four k horizontally and then I three k vertically sell like all my videos, they just so professional.

And then I also has that gamble, which is great for me because i'm always like literally on the run and i'm a very chaotic person. So IT helps like stabilized all my videos. Um yeah it's just an amazing camera.

And then of course, I have like the mix to the D J. I mix with the charging case. That pair really well, nicer with the it's great for like onsite interviews at conferences or I even use them for filming short form at my desk.

So yeah, she's a really great camera. I had my first one stolen accidentally, and I went and thought, IT again, that's how much I loved. IT was .

accidentally.

yeah. Well, I was actually purposes li stolen by someone. I lost IT on a train from booter pest to viana.

Yeah, was a sad day. They did. yeah. The viana police did not care. My camera was stolen, which is fair. They bigger problems.

But the sad thing is the content that .

was on the big lost. Yeah, luckily, like digger, I does have an apps. So I had most of my videos backed up to cloud.

So most backed up to the cloud and download on my phone, which a terror by the storage. So like most was backed up. But I did lose some videos from that up, which was sad. I was like, we, you can keep the camera, but send me back my memory card.

Yeah, all right. Just well, thank you for these hardware tips now as well. I have literally made a note in my shopping cart be purchasing these things and maybe I will have some great social media presence someday in terms of my video content um thanks just so much for agreeing to bear on this episode. I've enjoyed IT so much and yeah hopefully can catch up you with you again in a couple years and see things are coming .

along yeah that be awesome seeks so much for having me.

Awesome episode in IT just filled this on how SHE increased her salary from seventy two thousand dollars a year to over one hundred and fifty thousand a year or more than double that in the less than a year through building a strong case based on a responsiblities and market data.

And then during a company change by not revealing her current compensation, SHE also to talk about how her content creation journey began with a violent post about promote work leading to partnerships with major companies like IBM and S A. P. SHE. Talk about how for those entering data careers, how he recommends, starting with basic visio and statistics, then focusing on sequel as a provides transferable and really in a high demand skills.

Just to talk about how he advocates for women in them by chAllenging stereotypes and addressing sutter workplace bias like receiving appearance based compliments rather than technical feedback, as always, you can get all the shows notes, including the transcript, the episode, the video recording, any materials mentioned on the show, the else for jez, social video profiles, as well as my own. Add super da science, so com lash eight, three, nine and beyond media. Another way we can interact is coming up on december forth when i'll be hosting a virtual half day conference on agenda I it'll be interactive, practical and ideal future of some of the most influential people in the AI agents space as speakers.

You don't miss this one. It'll be alive in the o rilly platform, which many employers in universities provide access to others. SE, you can grab a free thirty day trial over rilly using our special code, S D S pod two three.

We've got a link IT to that code ready for you in the shown notes. Thanks, of course, to everyone on the super detis ze podcast team for producing another fun episode for us today for enabling that super team to create this free podcast for you are deeply grateful to our response. Or you can support the show by checking out our response or links which are in the show notes um and if you yourself are interested in sponsoring.

And so you can get the details on how to do that by making your way to john grown podcast otherwise share the episode people who'd like to hear IT review the episode wherever you listen to your episodes. Subscribe, obviously, if you're not a subscriber. But most importantly, I just hope you'll keep on tuning in.

I'm so grave to have you listening and hope I can continue to make epo de love for years and years to come until next time. Keep on looking out and looking forward to enjoy another, and thank you. Very zone.