Insights on the Intersection of Data Science and Bitcoin

Welcome to TechMinds.

Happy to be here. Cool.

Would you mind giving a bit of an introduction first about yourself so that the, the listeners know who you are?

Yeah, so I'm Chaitu. I've, um, I have a pretty international background in terms of my parents coming from India, but I happen to be born in the Netherlands because my dad worked for a company called Shell that many people have heard of. Um, and throughout my life I lived in different parts of the world, like in East Asia and in the US in California, and then in my adult life I've lived in various European countries and now find myself in Portugal. In terms of my background, I studied computer science in the Netherlands in a university called the Delft University of Technology. So I was always into sort of tech and computers from a fairly young age. However, once I actually went through university, I realized I'm not really the the hardcore programmer type. So becoming a software engineer wasn't so much my thing, but I did like kind of the mindset of data and of things being structured, of information being structured. So that appealed more to me. And luckily, that was around the time I graduated and joined the working world. That was around the time when data was sort of dubbed as the new oil. So there's been a lot of development over my sort of 15-year career in the data space. So I'm sure you'll have some specific questions on what you want me to talk about. Good.

Yeah, it's quite funny to hear sort of data is the new oil and then the background with Shell. So oil and Shell, that's a good one.

Yeah, it's quite funny. And then like I spoke to you, Stefan van Eerde, offline, I'd like to talk about Bitcoin as well because I think the next step step, then Bitcoin and AI are kind of the two new paradigms in the tech field from my perspective, but we'll get into that in a minute.

Great. Yeah, definitely, that will— that's something we definitely will be touching upon. So yeah, the first question that I have for you is, um, could you tell us about your journey into data analytics? What led you to this field, and also how did you transition across different industries like banking and e-commerce and cybersecurity? So can you, can you guide us through that journey.

Yeah, so like I said, I mean, once I was ready for the working world, I kind of knew I didn't want to go into the real software development kind of angle. So I was more interested in either human-computer interaction type things or data. And so as it turned out at the time, data was like a really sort of blooming area just in all industries. People were really trying to leverage the— that was kind of the time just pre-smartphone era, like sort of late 2008 is when I started working. That was around the time when companies were all kind of figuring out ways of how they can leverage all this internal data in order to just sort of provide more efficient and effective services and products to their clients. And secondly, how to capture more data in order to sort of maximize their business potential. So I think in a certain sense, it was logical just based on my interests and also on the fact that that's kind of the direction that all industries were looking towards. Yeah, in terms of transitioning from different industries, it wasn't particularly something that I planned or that I designed, but it just kind of happened by chance. I started my career working in consultancies, so Deloitte and KPMG. And so when you're in institutions like that, you tend to just go wherever the clients are. So I had some experience at a large telecoms company in the Netherlands called KPN, which is the largest telco in the Netherlands. And then when I worked, when I moved to London, then obviously banking clients are very huge there. So I worked in the financial services space for quite some years there. But then finally I got a job at eBay to work in their analytics team. And then I saw this sort of proper big tech side of how the data is used. And it was definitely a very big step up compared to these sort of traditional legacy banks in terms of how sort of data data intelligent they are and how well they leverage all their data. So yeah, it's definitely been interesting to see sort of how different industries based on how tech savvy they are, how much they sort of leverage their data. So in a place like eBay, you'll just have armies of analysts all working on very, very specific things, whereas in a bank you might just have 1 or 2 analysts that sort of do most of the things from an analytics perspective. So there's a lot of variance by industry. Good.

Yeah. And to tap on that as well, like, how did you get into eBay, for instance, like a big, well-known company like that? How can you sort of get into that organization? Yeah.

Yeah. So it was, so like I said, I worked in consulting, so I had experience at different clients, different industries. And then again, it's in my nature. I prefer to be more in sort of in charge of my destiny. So I became a freelancer actually. While I was working in London. So then I first started freelancing with the Royal Bank of Scotland and then brief contracts with other banks like Barclays. But I was always open to working in other industries. And once you've had a little bit of experience and you built up the right sort of credentials, as it turned out, eBay actually used a data warehousing tool called Teradata, which primarily was used by big banks. So I just happened to have the right sort of skillset that eBay was looking for at that time. And then that kind of worked really nicely. And for me, that was a real step up in terms of just being exposed to a proper tech company and, you know, just being exposed to big teams of analysts that are really thinking of analysts and analytics through and through, you know, of all, all elements of analysis from sales, you know, marketing analytics and, you know, all the channel attributions of their traffic and all the different ways of looking at conversion rates and how to optimize that. So it's a completely a different world when you're in a pure tech company versus a bank that's just trying to check whether all the customer data is populated and whether there's any data quality issues, you know, very basic stuff. So, um, yeah, it was just by chance and by, uh, by sort of experience that I slowly made my way up into the tech space. But if somebody's new in the space, I would always advise try to find a tech company or a startup company to work, work for from the beginning because you're just going to learn a lot more and they're just much more tech savvy. They typically have the best, um, tech stacks. So you learn like the most up-to-date and the most relevant tools that are kind of hot and in, in the moment rather than very legacy tools that banks will be using.

Great, I think that's very good advice for the audience. So thank you for this little sidetrack question. So we didn't prep this one, but, uh, I knew you would have a good answer on this, so thanks. So, um, another question I have is regarding machine learning. How do you see the role of machine learning and AI evolving in the data analysis field?

Yeah, it's, it's been one of these funny, uh, funny topics where it's sort of gradual and then sudden. So I worked with some data scientists, uh, before I joined eBay, and it suddenly seemed like all of a sudden there was this whole flood of all this new technology, all these Python libraries, all these different sort of data science kind of disciplines, uh, within the whole broader data umbrella. And, and now with like sort of the proliferation of AI tools, it's almost like, you know, you have to almost be ready for a paradigm shift where, you know, you could be an analyst at a company, but you actually have an, an army of analysts working for you if you have an AI tool. Like, you should, if you haven't already, you should just go try on Claude or on ChatGPT or any of these tools. You can give it any, typically any of the, um, take-home assignments that any company will send you if you wanna be a data analyst or data scientist. Just literally upload the document, tell it to answer the questions, and it'll probably get 80, 90% of the queries and the code correct. And so you can already from a very early, early stage act almost like an analytics manager, 'cause AI just gives you an army of analysts, or even if you're a software developer, it gives you an army of coders to work for you. And then you have to have that like kind of higher level judgment of just, okay, there's something wrong there, or that's clearly an AI hallucination, but all of this is correct. And it's just a complete paradigm shift because you can be a lot more efficient, but at the same time you need to actually have a higher level understanding of actually asking it the right things rather than just being tech savvy and good at writing SQL code or Python code. So it's a complete paradigm shift already and it's been quite sudden in the last, I'd say about 2 years.

Yeah, that's great. That's also a great balance that you have between expertise and, you know, let the AI tooling help you with that. But if you don't know, you know, if it's crap in, crap out, you know, you're not gonna—

Yeah, so you do need that little bit of experience, obviously. Like, you need to understand SQL or Python and things like that, otherwise you have no way of verifying that it's correct. But once you do have that little bit of experience, then your sort of path to sort of moving up and doing more interesting things and managing more interesting analytics problems is actually much more wide open because you then have that army of AI analysts to do all the groundwork for you. And I'm finding that on one hand, it's quite scary because what did I spend like 10 of the 15 years that I've worked doing because now the AI does it better. But at least I have that experience. So then I know what questions to ask it. So it's already for people that are sort of joining the workforce, you should really try to think also from a higher level perspective of what is the bigger picture, what problems am I trying to solve, uh, and then, you know, just being able to employ the AI tools to like do a lot of the, uh, the grunt work for you. Cool.

Yeah, thanks. Now on to your favorite subject, Bitcoin. Um, with Bitcoin's evolution, uh, over the, over the next the next couple of years, but also based on the past few years and things that are happening right now, right? So are there any emerging paradigms you're particularly excited about?

Yeah, so I mean, Bitcoin is, it's a very unique thing. I would liken it in terms of its importance to like the, the, the dawn and rise of the internet itself. And actually, if you, um, if you plot a curve of internet adoption and then you superimpose the Bitcoin adoption curve, it's almost identical. So we're probably still in the dial-up modem phase, if that means anything to anyone, uh, of internet adoption. But that's where we are on the Bitcoin curve. But we're probably going to see a very, very sharp rise in sort of interest and adoption and proliferation of Bitcoin. And I think you have to kind of step back and think what's so interesting about it is that in tech and in IT and internet, we, we basically have, um, abundance. So any book that's ever been written, any piece of music, any movie, it's all available at a click of a button, you know. And you can make copy-paste a million times for free, basically everything. And now with Bitcoin, you actually have digital scarcity, which is the opposite. Like, you have 21 million units and you can't copy-paste it, you can't fake it. And that's actually like from a paradigm shift perspective, that's mind-blowing because digital, you always think of, you know, abundance, but now you actually have something that's truly digitally scarce. And I think 99.9% of the world still hasn't understood that and what the actual implications of that are, but it's going to completely change the whole financial world for sure. It's going to change even Even things like, I think, real estate and all that is going to get completely disrupted over a longer time horizon. Because why do people speculate on real estate? It's because the money is defective. It's because a few insiders in central banks and governments can flood the market with money that they print out of nothing while the rest of us have to work 40 hours a week for our money. And then suddenly our money gets devalued overnight. And so Bitcoin doesn't allow that anymore as long as enough people adopt Bitcoin. And so it's going to actually bring a whole new type of abundance once enough corporations as well as individuals and countries adopt Bitcoin. So it's just going to be on the same scale as the internet. It's just that most people haven't figured it out yet. And then that's going to go hand in hand with AI because at the same time we have this AI revolution. So, you know, some of you might have seen the Tesla robots demonstration a couple of weeks ago, and many of us will have a robot like that in a few years in our house doing all of our cleaning and our cooking and our vacuum cleaning and whatnot. And so you have to think, we're going to suddenly have all these effective machines automating our SQL queries to our cleaning, to our cooking. And at the same time, we have like a proper hard money like we had back in the days of gold to store all of our value and not be sort of robbed by central banks and careless governments. So it's going to be a huge paradigm shift when you take the sort of AI and the Bitcoin combination together. And yeah, you have to be creative to think, to sort of imagine what kind of world we'll live in. But I'm optimistic about it and I think it'll actually free up people to do a lot more creative things rather than a lot of the grunt work that we have to do now.

Yeah. And it's already clashing with the status quo and more of it will happen probably in the foreseeable future, I think.

Absolutely. There's going to be a huge fight back, definitely from central banks, from financial services insiders, and just from the so-called elites. But the lovely thing with something like Bitcoin is that it cannot be stopped, just like with the internet. Good luck trying to ban the internet globally, or even things like BitTorrent, which are used for primarily illegal things, has never remotely been close to being banned because it's just not possible.

Interesting things indeed. So when it comes to someone looking to move from one industry to another within the data analytics realm, what advice would you give to someone looking to transition?

Yeah, I mean, my advice generally is don't be fooled by whether it's an industry saying that you need to have specific experience in that industry or a company specifically saying, oh, you have you have experience with Oracle but not with SQL Server. To me, that's all noise. As long as you're a good analyst or you're a good software developer or you just, you understand the tech, you can work in any industry in my view. You can work with any tool. Like if you use one variant of SQL versus another, or even in Python, if you're familiar with Python but you haven't used a particular library, to me these are not blockers at all. And I don't really accept when companies or industries put up these sort of fake requirements about these kind of things. For me, so, you know, you should just be looking at what you find interesting in terms of industry, in terms of company, and just be going for that and not let that be a blocker in your mind. I don't think it should ever be a blocker regardless of what area of tech you're in. Good.

Yeah, my own experience also with when it comes to these vacancy lists and information there, it is to find a good excuse to say no to someone they don't like, right? So that's why they come up with this huge list. Then there's always something to pick from to say, oh, you don't really comply with part number 4, part number 7, or whatever.

Yeah, or they just want to use it as a way to negotiate your salary down, but don't buy that either. You should just apply, be confident in your skills, and be confident that, you know, if you know the sort of the programming language or whatever it is to the right degree, then a certain different environment or a different tool it doesn't make a difference. That's never an excuse, and the companies shouldn't be using that as an excuse to try to pay you less or not offer you a particular role if you have the right skills.

Yeah, so it's really about the right skills. And also, for everyone listening, don't be shy, just apply. Even if you see that already 40 other persons applied or something, it could be that they could be less qualified than you. So just, you know, if you really go for something that you'd like, I'd say just go for it and just give it a try. You know, you have nothing to lose.

So yeah, I would add to that that once you've been in industry and various industries like I have for quite some time, you find that there are a lot of people, especially in big companies, there are a lot of people in jobs that they have no business doing or that they have no qualifications for at all. So you'll have, you know, in a consultancy, say like KPMG or Deloitte, these are originally accountancies, right? Their main focus is accounting and tax. And so you'll have some guy that's been an accountant for 20 years who's suddenly head of a data team and has absolutely, couldn't write like a simple SELECT query to query a table. So never let any of these kind of things be a blocker in your mind because you'll end up finding that there are a lot of people probably telling you what to do who have no idea about any of this stuff either. So just always go for what you're interested in.

Amazing. Great advice, I think. So thank you for, uh, thank you for being here with us and, uh, and helping enlighten this audience.

And it's been a pleasure.

And enjoy your time in Portugal. It's not the best place to be at, I guess.

So, uh, yeah, it's terrible. It's— the sun is shining again.

Great. Um, I see a question from the audience also coming in. How will we use Bitcoins in our daily lives? Do you see the possibility of it replacing real money?

Uh, yeah, absolutely. It will, uh, replace real money. Uh, so if you actually think of it, uh, humans were using gold for about 5,000 years, and now we have this brief period of about 100 years, uh, less than 100 years that we have this sort of paper money that's backed by nothing. And then, then we'll have another 5,000 years of Bitcoin. That's kind of how I see it. And so when we look back historically, we'll see this little blip in, in our history as, as the anomaly actually. And in terms of how it's going to replace money, well, of course, there's many stages to that. So initially, people will use it just like they still use gold today as a store of value. So one of the reasons you see all this inflation, everybody's aware of it now because the governments are just printing money and misspending money willy-nilly. And so a lot of the actually insiders and the elites and big finance people, they're all buying gold and Bitcoin because they know it's a way of storing value. Not getting caught by this inflation. Once there is enough adoption of the store of value curve, then you'll move to the sort of the medium of exchange curve, which will be— then you'll have your PayPals and your other applications on top of Bitcoin, which make it easier to, um, to transact and to buy your coffees or, uh, whatever. So you'll have sort of other protocols that sit on top of Bitcoin. Um, so that'll come in the near future, and whatever your opinion is of the, uh, the, the Trump result, the people around the Trump administration are actually much more pro-crypto and Bitcoin than, than the, uh, the Democratic Party was. So actually, there should be a lot more positive development on that front, uh, with the new administration. And that'll again put pressure on the Europeans to not try to regulate everything to death. And so hopefully we'll see a bit more activity on that front. And then finally, you'll have the third adoption phase which will be the unit of account adoption phase, where instead of pricing things in dollars or euros, we'll price everything globally in Bitcoin. And that's how it used to be with gold. And then you never had all these weird foreign exchange markets between, you know, pounds and liras and guilders, because everything was actually backed by gold and everything was stable. And hopefully we'll go back to that, and it'll take out a lot of noise from the financial system. Awesome.

I hope this answers your question, Meraer, if I pronounce your name correctly. So let me check if we see other questions or comments from the audience. I think for now that's it. So again, it's been a pleasure having you here with us. Thanks for being here and best of luck with everything, and hope to see you again anytime soon.

Great, thanks. It's been a pleasure.

Great, take care.

Bye, guys.