Hello. Um welcome uh from my side as well to the women in Tech Global Conference. Apologies for some uh technical issues that we have just encountered.I am uh genuinely uh delighted to be able to have this, you know, opportunity to share my story of how I transitioned into, into data. Uh Because I fairly recently uh and within this short dog that uh I will be having, I will be um uh touching upon the diver, the importance of uh diversity. So why it is important um to have diverse teams, not so much, not so only with uh more women participation, but also other minority groups, then uh we will move to uh me sharing the story of how I started my uh professional uh career and then um also shed some light on um important aspect of once, you know, somebody's already has entered the field.

Uh And I would like to touch upon the importance of mentorship. Um Yeah, so let us start with the really important um topic uh not just nowadays. Uh But yeah, uh we always see especially in tech that there is a lack of um different minority groups. Uh you know, uh working and also making important decisions. So let's first say why and discuss why diversity matters, right? So we can see that uh while women uh make a nearly, you know, half of the global workforce, they represent only 30% of uh it employees. So of course, this number varies um on the report that you would look at, but some around 130 is quite common. You would see uh that's uh pretty low, a number of women participation. Uh So here more or less focused on the women uh and not other um minority groups and why, you know, uh lots of companies, you can see a lot of uh talks uh that there should be more uh inclusion, right? So why is that important? So various studies show that um diverse companies uh perform much better. Um So financially um hire better talent and have much more engaged employees, right? So once we have much more diverse uh themes working on specific projects, it's also critical as it enables for the products that specific companies or services that they develop or produce uh are much inclusive, safer. Um that everyone or most of the people would take into consideration.

There was one study done that uh saying that more gender diverse companies are around 48% more likely as I said before, uh to outperform the uh least uh gender diverse companies. So this just briefly, I I thought it would be great to start or kick up the presentation with having, you know, um or touch upon this important facts. Uh Before I share, start to share my story and here is a chart of uh women uh participation in tech industries, right? So what we can see here is the hard we go when it comes to the um uh let's say seniority levels in tech, less of participation uh of women. We see and ideally, right, um If we could do more about, about that too. So um I would like to share also how I started uh with my professional career, what I'm doing currently now and also the process, you know, the thinking and all the experiences that led me to um try and be and try and also uh work in data and how uh I actually found it to be.

Um And yeah, exciting and rewarding field to be in. So I started a couple of years ago in European parliament uh where I was working for a few months in the T GB uh working on, yeah, making drafts for budget of 2018 you know, present or joining different kind of plenary sessions and be of help when it comes to that. Uh Shortly after I joined the BITS stamp, which is one of the oldest Cryptocurrency exchange where I was um business slash compliance analyst, um analyzing uh different kind of crypto movements in the market. And so, um and then destiny took me to revolut, which is uh a fin tech company, offering a whole host of uh products. Also there, I started as a business also in compliance roles at the beginning. But then throughout years move into more technical um roles. So after I left actually a few months ago, so I was, when I left, I was more much more in technical uh engaged or working on technical projects. Indeed. And I'm super uh delighted uh and uh grateful to um be working at Adian, which is a uh payments, um provider, payments uh company.

Uh And what I do uh specifically or currently is uh so my tasks revolve around operational and uh development uh tasks uh around um looker. So L is A B I two and why I find it so um exciting as I can, yeah, learn more about data on the job. And also while in addition to that also um continuously upskill myself by doing any kind of projects. And so, um and, you know, put all the, let's say the things that I have learned so much in practice and it's still in process, right? So I would say I'm still at a very early age uh or not age but process. Uh but nevertheless, it's super exciting to um to be, to be working in the data field um and uh learn a lot. I would uh I thought it would be great to um to share also how I, you know, started um or diverted to more to data field um and some suggestions or how, yeah, some steps uh that allowed me to um to be also, you know, somehow uh thriving, let's say so. So I think what I first um quite some time ago I thought it, it's really important to think about, you know, or I thought about my interest and um what would be the best way to start, right? So I think that is uh pretty crucial.

Uh And then I started to work on a simple projects. So um back like a year, maybe less than a year ago, I started to work on some um projects, really basic ones. And I did that by following specific or like youtube, um let's say um influence or data specialists who have their own youtube channels. And I just followed along. Uh So that was one thing uh that I did and another way of how I could get to know different kind of aspects of what's happening within the data domain was to um connect with the professional data experts who have years and decades of experience was to um organize uh different kind of events.

So what I do uh I, I organize a conferences or events within uh we, so which is like a initiative by Stanford uh and also by Deep learning initiative, which is uh a um initiative uh started um that started in 2017 by Andrew NG. Um So what I do is invite uh various speakers who operate in data science uh fields or also tech, we could say, right? Um And by doing so, I not only of course, get better organizational skills but also get to know the respective areas better. Um I wouldn't say in depth, but at least I know get to know what's happening in. Um uh For example, I had some projects about or events about machine learning about recommendation systems and things like this. Um uh And of course, by doing so, uh you also get to know what's um if that maybe could also be something that would interest you, right? Um uh Then I think what uh why I found why I actually find working data uh really rewarding and exciting uh so far. Uh um Is that one part that is uh super exciting is the whole process of problem solving. So for example, um that's something I also get to hear from more experienced professionals or experts and machine learning engineers is that, you know, once you're giving that specific um problem that uh you work on um for your stakeholders within the company or so is um yeah, while you are solving, especially after you solve it, there is a tremendous feeling of yeah, achieving making, making an impact um making that you made a difference.

So that's something that is deeply rewarding. Uh I would say uh the another thing is um while solving uh your specific project, you get to work with a whole host of different stakeholders. So depends on the project that you would do. Um But so within the company, as outside, you would get to know um yeah, talent people or get to uh um and by doing so, not only yeah, work on the project, but also learn new things which is uh super exciting uh as well. And last but not least there is an option or ocean of possibilities, right? So once you start, maybe let's say as a data analyst or so, doesn't mean that um you know, your fate is to be there forever. You have so many options um to um to test um or to try um of course, considering that you are upskilling yourself, that you're learning new things and you um maintain your curiosity. And so this is one part, right? When you enter the field and uh another um I think would say really good ingredient for somebody to also thrive in the new um data position or that position is uh from my perspective, also importance of um I or mentorship. So um the mentoring, mentoring is, is like a pillar of support, right? That uh this can be done via professional groups or one on one.

And there is also um some interesting facts um that mentoring can boost, you know, uh it can be an effective way of boosting diversity. And um there was a study done that shown that um they boost the representation of women and minorities uh by 9 to 24%. But here, I'm not, you know, I wouldn't like to um focus on diversity groups. I think it's all very important to have mentor um when starting, especially when changing a career. And another uh super exciting and important thing is that mentorship can improve, you know, um employee engagement um And can, you know, create an organization which learning becomes a part of uh overall culture. Um So, yeah, I think that is uh super important for somebody not just to um you know, upskill themselves to learn new things, but also to thrive in, in the field. So that's um briefly uh from my side. Um uh I'm open for any questions and again, apologies for a bit of uh disruption at the very beginning.

No worries. It is masterful without slides. I didn't really enjoy listening to you. And so everyone else, we have a question. But before we go and take the question, I would like to say that something that resonated with me. I think what you said, making an impact is deeply rewarding and I'm working with different stakeholders and how it really helps to learn something new. And I think something new that they learn today how to deliver a presentation without slides in a really impressive way. So thank you so much for doing that. And let's take a question from Sushmita. So she's asking how do you deal with problem solving when you don't have sufficient data?

Ah Good question. So at the moment, uh I am um uh um B I specialist so or B I administrator in A in. So that wouldn't be uh the, let's say one of the problems that I would encounter. But I would, in this case, how I would approach it is to take with the stakeholders um to get the sufficient data or maybe if I could have like a sufficient uh maybe sub question would be um meaning like um data for uh uh by the time horizon or so. But I think I would just go back to the stakeholders um and try to get more, let's say data for the for the project that uh I have been assigned to or that I would be working on. I hope it just ask

and it's just said work and like being able to reach out to stakeholders. I think this is really good. OK, fantastic. And I think uh Madia just confirmed my statement about you doing a great job even without presentation. So congrats to you, you should be proud and thank you so much for joining us today. Everyone who's listening to us to make sure to drop by, by AAA Booth and say hi to Bridgetta if she's there. Thank you so much Brigitte. I also will drop you linked in so people can connect with you and thank you for being with us, stay with us for the rest of the conference.

Thank you so much. Would you like me to share the presentation uh or the slide? Yeah, if you, if you can,

if you can share a link, for example, if you have a shareable uh document, so you can share it just in the chat. I think many people would love to see. Fantastic. Thank you. It was a pleasure to have you. Bye bye bye.