Episode Twenty Eight: Key Skills for Working in a Data Environment

Challenge Everything in Data to Understand its Meaning

Challenge everything, understand the meaning and the reason behind it.
 

In this episode we are in conversation with Leyre Murillo Villar, Data Management SME at Macquarie where she discusses her early experiences in the data and financial services industry, the rewarding and challenging path of a career in STEM and attracting young female talent into the data field.

(Please note that this podcast was recorded prior to lockdown and at the time Leyre was CDO Data Control Lead at BNP Paribas.)

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The Power of Data Podcast

Episode 28: Key Skills for Working in a Data Environment

Guest: Leyre Murillo Villar, Data Management SME at Macquarie Group (Previously CDO Data Control Lead at BNP Paribas)
Interviewer: Louise Cavanagh, Communications Director, Dun & Bradstreet

Louise 00:00
Welcome back to the Power of Data Podcast. Today we're at the Women in Data conference in London. I'm delighted to introduce our guest this week Leyre from BNP Paribas. First of all, massive congratulations to you for being one of the winners of the 20 in Data and Technology award.

Leyre 00:15
Thank you.

Louise 00:16
And related to that, I wondered if you could tell us a bit about your role in data and analytics, and also a bit about your career path and how you've got to that stage.

Leyre 00:25
First of all, thanks very much. It's a pleasure being here and it's an honor to be one of the 20 in data technology 2019. So I work in BNP Paribas as the Chief Data officers Data Controller. So BNP has different data offices across the business, technology, architecture, risk, finance, etc. So we are a huge network of data offices and BNP Paribas, a very, very big group. So it's pretty challenging to make sure that we are all aligned and we work with the same objectives in mind. So I've been with BNP for four years. Now, working with global markets, I sit within the business. And one of the main priorities being in the data office is making sure that we are very, very close to the business we realize the objectives of the business by using the proper digital and data strategy, meaning data governance, policies, roles and responsibilities, also Data Quality Framework, data control environments. So it's a little bit of everything, also without forgetting the regulator, so regulator is one of our main actors, our main clients, I will say and we know the regulator is there we know there are many things to do in order to comply with the regulator and the need for transparency at the same time of the need of proper management of the personal data, as well as the need of giving to the business clear and quality information so they are able to make the right decisions on time in order to make money, one of the main goals of any business. So it's pretty challenging, a lot of exposure and a lot of impact. But definitely working in a data offices is a pleasure. It's fun, it's challenging and it's rewarding every day. It's rewarding because I get to work with so many different stakeholders, know the organization back and forward, end to end all the business processes, technology and architecture ideas. I'm so happy to be working in this in this environment.

Louise 02:30
And that's something we found from our other conversations with other interviewees is that data is just so intertwined in every part of every business, you can’t escape it and it's only going to get much more so I think going forward into the future is it's you can't escape data, it's everywhere around us in our personal life and our business life. It's so critical to success.

Leyre 02:48
Yeah, exactly. And it's not only that we need it, we need to govern it. We need to know the data that we have all sorts of data in financial services, we talk about structural data, client data, employee data, transactional data, risk data and of course, financial data. So any type of data we have, we need to know with government know where it is, where did this come from, who is using it, to what purpose is using it, and how we can get the most of it in order to predict certain things. And this is where analytics comes in. So you can have the most wonderful and amazing analytics tools and AI tools, but if you don't input those tools and feed those tools with proper data, or the data structure and clean and good data, your analytics tools are not going to give you the answers you need for your purposes.

Louise 03:44
It's a good data in and good data out type of thing!

Leyre 03:46
Yes, if you have rubbish data in, you may have rubbish data out. So I'm very happy to be working in this type of environment. And also get to know what other colleagues are doing in events like this.

Louise 03:59
And today's a great opportunity for women. And there's men out there as well who are at the conference in the industry to share experience and insights. And I think there's a real buzz out there. It's such a great event to be at. So talking about the event, and obviously, the theme is around diversity and attracting more women into the industry. Could you tell us a bit more about how you approach diversity in terms of your team and how you're looking to sort of attract women and other sort of underrepresented groups into your team and how you supporting them?

Leyre 04:27
I'm very lucky because in BNP, across the data offices, the number of men versus women is pretty much the same. It's balanced. And it is true that a company like BNP is investing a lot in measures to fight against the gender parity gap. And we have one of the Sustainable Development Goals, the fifth one is gender equality. So BNP is really supporting all these goals. In terms of in my specific case, I am part of the Woman in Global Markets stream. Specifically the recruitment stream. So what we do is we will, of course, there are monthly meetings. And what we do is we tend to participate in interviews with young woman younger that are at university or finding and trying to find the their first experience in a working environment. And we try to explain them that they shouldn't be afraid of working in financial services. In this case, it's specifically for financial services not yet data. But anyway is we try to explain why they shouldn't be afraid of working in financial services that no matter what the background is, and it applies also to data. You don't necessarily need to have a studied computer science or mathematics in order to join the data workforce or the data space. Same for financial services. You just need to have the passion the willing to work in a in a challenging and changing environment and the social capacity. Be willing to learn new skills. So that's what we do in the recruitment stream. We have interviews with young girls, we try to attract them to the Financial Services, we try to tell them that they should apply to jobs in financial services. Also, we have networking events. So it's a kind of trying to attract more people and try to get more people to apply for positions within BNP. That’s the things I'm doing at the moment. And as I said, we envisage a huge ambassador of everything that regards gender parity.

Louise 06:32
It's great. I mean, that's the thing of responsibility for big businesses like us, like Dun & Bradstreet and BNP, it's that we have a responsibility to take that on board and treat it as an important issue. And if more and more companies do that, then hopefully the change will start happening faster.

Leyre 06:48
Yes, it has been like that for me, but it hasn't been like that in the past in terms of, of course, I studied computer science and in a small city in Spain, so I don't remember the exact person that they were but during all my life I've been surrounded by men. And so during my studies and then in my early days of work, working in, in the data space, data science and I did my masters in in artificial intelligence at that time, where it was not as trendy as it is now. But for me the thing about for me it sounded fun, artificial intelligence, yes I'm going to do that! And then I started working in Deloitte, then I moved to EY but always in financial services, slash data science or data analysis or data quality environment, but I didn't realize it at that time. I was like, yeah, well, it's natural, right? Because it's a men's world is a men's career. So it's natural to have all my stakeholders being men, well maybe not all but most of my stakeholders are for me. So when I found a woman that it's in a senior position or in a pretty subject matter expert position role. For me, it's very attractive. And it's like kind of a role model as well. And I want to be like that. And if this woman has been able to reach this position, I could do it too.

Louise 08:10
And that's something that a couple of people have mentioned today is that having a role model and a champion or feeling that it's okay to aspire to be want to be like, the sort of pressure of the fact when that's not there and it is a male dominated area, feeling that it's harder to have that self confidence to do that.

Leyre 08:28
Yeah.

Louise 08:29
You've got just as much right to be there as anyone.

Leyre 08:32
Exactly. And it's nice to have these type of examples. Because you can see you can do the same, and also pick up the right skills and the right behaviors. It can lead you to become a better person and a better professional.

Louise 08:47
Yeah, and the thing you mentioned about skills, so the mathematics and the computer studies aren't necessarily a prerequisite for all roles in the data industry. What do you think are the sort of behaviors and skills the sort of wider skill set?

Leyre 08:59
So first of all, I would like to clarify, studying a STEM subject, it helps. Because when you study in a STEM side, I will welcome I will encourage all ladies or many ladies to study this, don't be afraid of it, any STEM subjects or careers because they are very rewarding, challenging, and I would say they help build your mind and make your mind a problem solving mind they teach you certain skills that then you would be able to apply anywhere. That's the thing when you study a technical career or you pursue a technical career, it doesn't mean to say that you are going to end up in a lab or you're going end up in uni teaching math’s. You can apply those skills anywhere to any industry, pharmaceutical, health, insurance, financial services, retail environment, climate, any type of industry, you can apply all those skills and at the same time, if you don't have a technical background doesn't matter. Because if you like asking questions, getting to the root cause of the problem, you enjoy solving problems, applying logic. Having networking skills is also important loving to talk to people find out what they do understand really understand things really understand things when you do them, not just two things because they have to be done. Challenge everything, understand the meaning and the reason that is behind. So all of these type of skills help in working in data environment and in the data space. And then the technical skills, if you haven't learned them at uni, you can easily learn and there are many online courses, many, many, many resources out there where you can pick up the technical skills, if you need them. I know many data professionals that don't use the technical skills at all, because they are in more in the management side or more in the data governance side. Not everybody needs to be a data scientist or a data analyst or not everyone needs to code in Python. So there are different sorts of profiles and roles in there. But going back to what you said before is true that they ties the future. So I remember when I was a student, and I was a teenager, I didn't know what career to pursue. I didn't know what to do with my life. And I remember my dad back then telling me, yeah, computer science is the future. And data is the future. So you choose to do that. And I was like, yeah, I haven't touched a computer. So I don't even know what you know how to write how to type. He was right. So now, thanks for that. So I mean, that, of course, everyone is saying the same. But we don't know what's going to happen in 5-10 years. 20 years, we don't know. But we need to be ready for that. We need to be prepared for that on what it's true is that data is going to be there any type of data and the more we are ready to do that, the more we are resilient, and the more we are attached to this type of thinking, data is going to be there. So every day there are more young women that are joining the workforce every day, or every year and they are bringing all these new skills, new technological skills, new things are happening in the market, knowledge of FinTech everywhere. I guess what I'm trying to say is that data is there. And we need to understand that today we don't know what's going to happen and we don't know what all the skills we may need in the future. I don't think robots are going to take over the world, they take all the jobs so things like that I'm not scared of robots, robots is just is a person that has written a piece of code that runs automatically, that's it, but we need to be able to go with the flow and be flexible and I’m a data geek, I love it. I love it in my work life. In my personal life. I think my mind is kind of structured that way. Everything I do I transform it inside my brain in a process or in an in a table in an Excel with variables and with flux and with everything is there and my mind is like yeah, like crazy. But of course my job we need to change and my skills will need to adapt to new times.

Louise 13:02
It's a really important point is it being ready for what the future brings? And, and having the sort of skills and resources and the flexibility to take that on. I think what you said about diversity as well, in terms of the data industry, I mean, the data shows us that having a diverse team, we've got biases in data and things like that, so it's a fact it's a step that if we have more diversity, we're going to be have a better perceptions, different viewpoints on things, even though it's still crunching numbers and looking at data. having different people doing that brings a different level of depth to it, I think is really important. I know you've got to run back into a session. And it's been really interesting talking to you just one final question to sort of close on. If there's someone who's given you a piece of advice, or something that's inspired you in your career that you'd like to leave with our listeners as kind of something they can take with them..

Leyre 13:50
So I've had different managers in my life, different line managers, different bosses, and each of them with a different level of seniority. I’ve been very lucky because all of them have given me time. And one thing that I admire in most of them in the ones that I admire, of course, is that they were always willing to listen, they would always listen to what I had to say, even though they had made their own decisions. So I think that it's a good thing to listen to the different options. That's why the diversity factor is very important. So having a good blend of different options, listen to all of them, and then make a decision based on the data and the analysis of the different options. This is one thing that I've learned from my mentors and leaders, like listen to everyone, senior people, also people that are hands on, see the different perspectives that they have, and then make a decision based on an analysis of the full scenario, even though it's very difficult to control all the variables, and also to the young woman that would like to enter the data space. I would tell them that they shouldn't be afraid of making mistakes, because they will. They will make mistakes. I'm from my experience, I've learned that, it's like an artificial intelligence, the human intelligence work like that, you make a mistake, you learn from it, you go back, and you input this information that you've learned from the mistake to go one step forward and try something different. So it's like, don't be afraid of making mistakes, because you will. And you have to give your teams and your people, your peers, everyone the opportunity of making mistakes, trying things, learn from them, empower themselves, and believe on their capacities, and keep learning.

Louise 15:38
That's great. I think that's a really nice, wise advice to leave our listeners with. And I just wanted to say congratulations again to you. And thank you so much for spending the time with us. We really appreciate it.

Leyre 15:49
Thank you. I appreciate to spend some time with you. It's been great.