 Hey girls and guys, welcome back to theCUBE. We are live at Stanford University, covering the eighth annual Women in Data Science Conference. One of my favorite events, Lisa Martin here. Got a couple of guests from Total Energies. We're going to be talking all things data science and I think you're going to find this pretty interesting and inspirational. Please welcome Alexander Le Pen, tech advisor of data science at Total Energies. Great to have you. And Miriam Faiades here as well, product and value manager at Total Energies. Great to have you guys on theCUBE today. Thank you for your time. Thank you for your sleepiness. Give the audience, Alexander, we'll start with you, a little bit about Total Energies, so they understand the industry and what it is that you guys are doing. Yeah, sure, sure. So Total Energies, the former Total, so we changed name two years ago. So we are a multi-energy company now, working over 130 countries in the world and more than 100,000 employees. So we're quite a big company and we, if you look at our new logo, you will see there are like seven colors. That's the seven energies that we, basically that are business. So you will see the red for the oil, the blue for the gas, because we still have a lot of oil and gas, but you will see other color like blue for hydrogen, green for gas, for biogas, and a lot of other solar and wind. So we're definitely a multi-energy company now. Excellent, and you're both from Paris. I'm jealous I was supposed to go. I'm not going to be there next month. Miriam, talk a little bit about yourself. I'd love to know a little bit about your role. You're also a WID's ambassador this year, which is outstanding. Give us a little bit of your background. Yeah, so today I'm a product manager at the Total Energy Digital Factory. And at the Digital Factory, our role is to develop digital solutions for all of the businesses of Total Energy. And as a background, I did an engineering school. So, and before that, I would say I wasn't really aware of, I had never asked myself if being a woman could stop me from doing what I want to do in the professional career. But when I started my engineering school, I started seeing that women are becoming, I would say, increasingly rare in the environment that where I was evolving. So that's why I started to think about such initiatives. And then when I started working in the tech field, that conferred me that women are really rare in the tech field and the data science field. So, and at Total Energy, I met ambassadors of the WID's initiatives. And that's how I decided to be a WID's ambassador too. So our role is to organize events locally in the countries where we work, to raise awareness about the importance of having women in the tech and data fields. And also to talk about the WID's initiative more globally. One of my favorite things about WID's is, it's this global movement. It started back in 2015. theCUBE has been covering it since then. I think I've been covering it for theCUBE since 2017. It's always a great day full of really positive messages. One of the things that we talk a lot about when we're focusing on theCUBE on women in tech or women in technical roles is, you can't be what you can't see. We need to be able to see these role models. But also, we're not just talking about women. We're talking about underrepresented minorities. We're talking about men like you, Alexander. Talk to us a little bit about what your thoughts are about being at a women in data science conference and your sponsorship, I'm sure, of many women in Total and other industries that appreciate having you as a guide. Yeah, yeah, sure. First, I'm very happy because I'm back to Stanford. So I did my postdocs with Margot back in 2010, so like last decade. I'm a field mechanics person, so I didn't start as a data scientist. But yeah, which is always a discrete event as you describe it, to see, I mean, it's growing every year. I mean, it's fantastic. And it's very, I mean, it's always also good as a man to be in the situation of most of the women in data science conferences. And when Margot, she asked at the beginning of the conference, okay, how many men do we have? Okay, can you stand up? Yes, I saw that. It was very tasty because we were like 10 or maximum. Yeah. And I mean, you feel that, I mean, you could feel what it is to be a woman in the field. Absolutely, yes. It sounds like you experienced it. I experienced the same thing, but one of the things that fascinates me about data science is all of the different real world problems it's helping to solve. Like I keep saying this, we're in California, I'm a native Californian, and we've been at an extreme drought for years. Well, we're getting a ton of rain and snow this year. Climate change. We're not used to driving in the rain. We're not very good at it either. But just thinking about data science as a facilitator of us understanding climate change better to be able to make better decisions, predictions, drive better outcomes or things like police violence or healthcare inequities. I think the power of data science to help unlock a lot of the unknown is so great. And we need that thought diversity, Maryam, you're talking about being an engineering. Talk to me a little bit about what projects interest you with respect to data science and how you are involved in really creating more diversity in thought. In fact, at Total Energies, in addition to being an energy company, we're also a data company in the sense that we produce a lot of data in our activities. For example, with the sensors on the fuel, on the platforms or on wind turbines, solar panels and even data related to our clients. So what is really exciting about being working in the data science field at Total Energies is that we really feel the impact of the project that we're working on and we really work with the business to understand their problems or their issues and try to translate it to a technical problem and to solve it with the data that we have. So that's really exciting to feel the impact of the projects we're working on. So to take an example maybe, we know that one of the challenges of the energy transition is the storage of energy coming from renewable power. So I'm working currently on a project to improve the process of creating larger batteries that will help store this energy by collecting the data and helping the business to improve the process of creating these batteries to make it more reliable and with a better quality. So this is a really interesting project. It's an amazing project and it's fun, I think, to think of all of the different people, communities, countries that are impacted by what you're doing. Everyone knows about data. Sometimes we think about it as we're always paying for a lot of data on our phone or data rates may apply but we may not be thinking about all of the real world impact that data science is making in our lives. We have this expectation in our personal lives that we're connected 24 seven. I can get whatever I want from my phone, wherever I am in the world and that's all data driven. And we expect that if I'm dealing with total energies or a retailer or a car dealer that they're going to have the data to have a personal conversation with me. We have this expectation. I don't think a lot of people that aren't in data science or technology realize the impact of data all around their lives. Alexander, talk about some of the interesting data science projects that you're working on. There's one that I'm working right now. So as tech advisor, I'm not the one directly working on it but we have, you know, we're from the digital factory where we make digital products. And we have different squads. I mean, it's a group of different people with different skills. And one of the squads, they're working on a project that is about safety. We have a lot of sites, work sites over the world where we deploy solar panels on the parking, on buildings, everywhere. And there is, I mean, a huge, I mean, but I mean, we have a lot of workers and in terms of safety we want to make sure that they work safely and we want to prevent accidents. So what we do is we develop some computer vision approach to help them at improving, you know, the way they work. I mean, the basic things is detecting some equipment like the vest and so on. But we're working to really extend that to more concrete recommendation. And that's one very exciting project because it's very concrete. And also I'm coming from the R&D of the company and that's one of these projects that started in R&D and now into the digital factory and it will become a real product that we deploy over the world on our assets. So that's really great. The influence and the impact that data can have on every business always is something that we could talk about that for a very long time. But one of the things I want to address is they're, I'm not sure if you're familiar with AnitaB.org, the Grace Hopper Institute. It's here in the States. And they do this great event every year. It's very pro women in technology and technical roles. They do a lot of studies. So they have data demonstrating, where are we with respect to women in technical roles? And we've been talking about it for years. It's been for a while hovering around 25% of technical roles are held by women. I noticed in the AnitaB.org research findings from 2022, it's up to 27.6%, I believe. So we're seeing those numbers slowly go up. But one of the things that's a challenge is attrition of women getting in the roles and then leaving. Maryam, as a woman in technology, what inspires you to continue doing what you're doing and to elevate your career in data science? What motivates me that data science, we really have to look at it as a mean to solve a problem and not to find a goal in itself. So the fact that we can apply data science to so many fields and so many different projects. So here, for example, we took examples of more industrial maybe applications. But for example, recently I worked on a study, on a data science study, to understand what, to analyze Google reviews of our clients on the service stations and to see what are the topics that are really important to them. So we really have a large range of topics and a diversity of topics that are really interesting. And that's so important, the diversity of topics alone. There's, I think we're just scratching the surface. We're just at the very beginning of what data science can empower for our daily lives, for businesses, small businesses, large businesses. I'd love to get your perspective as our only male on the show today. Alexander, you have that elite title. The theme of International Women's Day this year, which is today, March 8th, is embrace equity. What is that? When you hear that theme as a male in technology, as a male in a role where you can actually elevate women and really bring in that thought diversity, what is embracing equity? What does it look like to you? To me, it's really, I mean, because we always talk about how we can improve, but actually we are fixing a problem and issue. I mean, it sets the reality. I mean, and the reality and for us in the company, and that's I think in total energy, we still have things, I mean, we haven't reached our objective, but we're working hard and especially at the digital factory to improve on that. And for example, we have 40% of our women in tech. 40% of our tech people that are women. Wow, that's fantastic. You're way ahead of the global average. It's outstanding. We're quite proud of that. But we still know that we have at least 10% because it's not 50, the target, is to 50 or more. And but I want to insist on the fact that we are correcting an issue, we are fixing an issue. We're not trying to improve something. I mean, that's important to have that in mind. It is absolutely. Miriam, I'd love to get your advice to your younger self. Before you studied engineering, obviously you had an interest when you were younger. What advice would you give to young Miriam now, looking back at what you've accomplished and being one of our female, visible females in a technical role? What would you say to your younger self? Maybe I would say to continue as I started. So as I was saying at the beginning of the interview, when I was at high school, I've never felt like being a woman could stop me from doing anything. So maybe to continue thinking this way and to stay, to continue this way. That's excellent. I think you have the confidence. And that's something that a lot of people, I struggled with when I was younger, have the confidence, can I do this? Should I do this? And you kind of went, why not? Yes. Which is, that is such a great message to get out to our audience and to everybody else. It's just, I'm interested in this, I find it fascinating. Why not me? Yeah. Right? And by bringing out I think role models as we do here at the conference, it's a way to help young girls to be inspired and, yeah. We need to have women in leadership positions that we can see. Because it's a saying here that we say a lot in the States, which is, you can't be what you can't see. And so we need more women and men supporting women and underrepresented minorities. And the great thing about WIDS is it does just that. So we thank you so much for your involvement in WIDS. Ambassador, our only male on the program today, Alexander, we thank you. I'm very proud of it. Awesome to hear that TotalEnergies has about 40% of females in technical roles. And you're on that path to 50% or more. We look forward to watching that journey and we thank you so much for joining us on the show today. Thank you. Thank you. All right. For my guests, I'm Lisa Martin. You're watching theCUBE live from Stanford University. This is our coverage of the eighth annual Women in Data Science Conference. We'll be back after a short break, so stick around.