Interview with Giada Fusè, IoT Ecosystem Data Scientist – Haier Europe
Quickness to adapt, curiosity and a constant drive to never give up: here are the main characteristics of the most requested figure in today’s business: the Data Scientist. A professional choice balanced among various competences but, as shown by the recent studio by Boston Consulting Group “What’s Keeping Women Out of Data Science?”, still something uncommon for women. According to the research, in fact, women in Data Science represent only the 15% of the field. However, the number of female professionals who accept the data challenge, reaching important goals in leading companies, national and international, is bound to grow. Giada Fusè is one of them. After a career started in Finance, she joined the leading electrical appliances brand in the world, Haier Europe, as a Data Scientist. Here, with the IoT Ecosystem team, she contributes to product innovations and she’s designing solutions to satisfy the needs of the end consumers. We interviewed her to explore her vision on the evolution of Data Science, one of the most cherished branches in today’s business, and observe with her the landscape and the goals that the new generation of data experts is going to meet.
After a degree in Economics and Business Management and specializing in Finance in Bruxelles, what brought you to embrace a career in Data Science?
The growing awareness of my desire to start a career in a field that is “hungry” for innovation, fast to establish itself in the world and never boring. As a classical high school student, I had no idea I’d start a career in Data Science. Over the years, though, and not by chance, my experience has become more and more focused on “quantity” and step by step I inched closer to what was, and still is today, my main area of interest. It wasn’t a professional choice, started through a targeted educational path, but more of a life journey, growing closer and closer to the subject and everything about it: a path in constant flux. And I’m happy it happened this way. I believe that the maturity of gaining confidence with this role is one of the hardest goals that a Data Scientist could aspire to, but also one of the most fulfilling ones. A goal that is, obviously, in constant evolution just like the world we interact with every single day. This is why I never speak in past tense when I’m referring to a career in Data Science: it’s such a new world, with a great desire to “explode” and we must try to chase it and understand it. We are “the machines” of this evolution, we need to keep up at full speed, always experimenting but most importantly understanding that we will never feel like we achieved everything in our field. After all, this is what’s great about Data Science, don’t you think?
The Data Scientist’s role is a hybrid one: a mix of competences in information technology, statistics and business. Specific courses of study have started emerging only recently. We can say that the “first generation” Data Scientists belong to different types, according to their educational background. What do you think are the most important characteristics and competences to tackle today’s business challenges?
I like to think that the Data Scientist figure is perceived in the world as defined in 2012 by the Harvard Business Review in the famous article, “Data Scientist, The Sexiest Job of the 21st Century”: “a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data. […] Their sudden appearance on the business scene reflects the fact that companies are now wrestling with information that comes in varieties and volumes never encountered before.” I can only agree with this statement and I think that the words “training and curiosity” are central: an explosive mixture, one I can totally see myself in. In my opinion, these are the characteristics that need to coexist and be constantly and equally nourished. A Data Scientist needs to be ready to “take a leap” and be overwhelmed by a complex and fast subject, without ever getting tired of developing their training and curiosity. There’s one thing I’m sure of: in our profession, if you stop you’re lost! Ours is surely a hybrid role, but I also think it’s adaptable to every field. I want to point this out, because I come from a career in finance and moving to a completely different market, such as the one in which Haier Europe operates, has been incredibly surprising. Once again, I experienced the opportunities that this job can provide: before starting in Haier, I was worried by having to “set aside” all my knowledge in Data Science and Big Data in the financial area, which I had developed with passion and effort over the years. I quickly realized, though, that I simply needed to adapt it to a business model that, despite being different, is very similar regarding the applications of Data Science. This is what makes my role one of a kind. So I also feel that another key characteristic of the role is having observed Data Science through as many points of view as possible and being able to apply it successfully to the business, whatever it may be. It doesn’t matter what “type” of Data Scientist you are: what matters is learning from these differences and being able to extract the best aspects from each of them.
The first part of 2020 forced us to radically reconsider our way of living. How has the relationship between people and technology transformed? Are we ready to live a “smart” life?
I’m obviously biased: working in the IoT field, it’s easy for me to talk about “smart life” and its applications in our daily life. The advantages in being smart, in my opinion, are several and they can contribute to drastically improve the quality of life of people who accept it as a “lifestyle”. Still, the majority of consumers struggles to accept and integrate this approach in their lives. It’s scary that a new algorithm could surpass humans in an activity that has always been exclusive to them. Working on new algorithms every day, I realize that there’s a widespread perception about innovation that imagines a not-too-far future where human intervention is excluded. We’re afraid of becoming useless for the communities we live in, and this inevitably brings us to reject innovation, especially when it’s embedded in our daily habits. In my opinion, the problem is having the wrong concept of what being smart means. It isn’t a race towards innovation at the expense of humans, but a smart utilization of machines and algorithms in their favor, trying to obtain a tangible added value. We must not be overwhelmed by fear: machines have limits too! 2020 forced new habits on us: some people have benefitted from it, others haven’t, but it was a first notice of evolution in our way of living, in a society that requires flexibility and acceptance of future, perhaps sudden, changes. The world is evolving and we need to keep up, sometimes it’s not even a choice. Technology and innovation can help us to welcome and embrace the future in our lives instead of fighting it.
“Zero distance with consumer” is Haier’s iconic claim, and today it sounds even more powerful. What’s the role of data analysis and technology in removing the distance between brand and consumers?
Data is the most precious thing a company owns. It’s the first thing a Data Scientist learns and something that they need to “evangelize” inside the business. After all, without data, how can we know the consumers’ habits? How can we attract potential customers? How can we know what brought a tangible return on investment to the company? Or again, how can we keep our customers and study their habits to offer them a new product that responds to their needs? The role of data analysis “speaks for itself”: not only by predicting the future behavior of the clients and helping us in consumer oriented decisions, but also by supporting other areas of an organization such as Human Resources, Finance and Control, Production and so on. Technology needs to be the engine that powers all of this: the key to offer understandable data to the business, necessary to proceed with an advanced and effective analysis. Haier Europe is counting heavily on data as the enabler of business choices by decision makers, and “I am the machine” that produces the final output used to base the business observations. We Data Scientists are the communication bridge between the raw numbers and the final decision maker, and a tangible support in the definition of targeted actions, guided by the interpretation of data.
The promises of the Internet of Things for our wellbeing and health are several: in actuality, how can the integration of Artificial Intelligence improve our life?
The advantages of IoT applied to our daily life are undoubtedly multiple: offering comfort and ease of use of appliances remotely, saving time, improving our safety at home and outside, providing voice assistants that can guide us through our needs and so on. Despite the fact that the number of AI applications in real life is still low, as we have observed earlier, it’s luckily constantly rising, at least for Haier. People are starting to open themselves to innovation, for several reasons: there are some consumer clusters who are definitely more inclined to change, more curious and excited to use advanced technologies, and others that see in AI a tangible help they can take advantage of. Let’s think about working parents who need to save time, or people who use Smart Home to interact with multiple electrical appliances through app or voice control. There are also people who have noticed a change in their emotional state thanks to integrating AI in their daily life, as stated by a recent study by Dr. Kazuo Yano, Fellow of Hitachi Ltd., who believes AI can help us to become happier. This doesn’t mean that we need to transform human beings into robots, or our emotions in standardized or programmable impulses. Dr. Yano believes, for example, that an app can be useful to seniors to deal with loneliness and sadness. “Nobody would want to live 100 years with health issues and without happiness, but it would be a completely different thing to live 100 years happily.” I agree with an optimistic and romantic vision of AI as the solution to many problems that trouble humans. This kind of vision can definitely help us and give us a spark of hope we might be lacking nowadays.
According to the recent study by Boston Consulting Group, “What’s Keeping Women Out of Data Science”, only 35 of 100 women choose to follow an educational path in scientific faculties (so called “STEM”). Moreover, only 15% of them work in the Data Science field. What should happen in your opinion to level this huge gender disparity in the field?
Luckily, I’ve always had the chance to follow the path I wanted and this translates in a career that is seen as more “male-centered” but only from a statistical point of view (the figures of BCG’s study speak clearly). In my case, it wasn’t difficult to enter the Data Science world, as I was a female candidate chosen by men among many other male candidates. But I want to point something out: choosing a woman rather than a man doesn’t have to become a way to forcefully level the gender imbalance in the field, otherwise we’ll simply shift the problem the other way. I believe in meritocracy and I want to think that a woman gets chosen among other candidates, including men, because of her skills and competences. I don’t like to talk about gender disparity in a work environment because I trust that the choices, at least the ones who I’ve been involved in directly, have been driven by an objective analysis of my skills. Sometimes I ask myself: “Why is Data Science associated to a male-dominated job?” Is it only for “computer nerds”? Is it extremely competitive or maybe women have bigger issues in dealing with numbers? I could never find a reasonable answer, simply because there isn’t one. I think it’s a cultural issue: we come from a history where men have always been seen as superior to women, in everything, but we have also been able to evolve in time and start to balance that enormous separation. We still have a lot of work to do and, in my small way, I think I’m a “trailblazer” for the role I represent and I’m the living proof that Data Science can be fascinating to everybody in equal measure: a “multicolored” subject that involves countless aspects and nuances in the type of roles. In conclusion, Data Science is definitely not a world that wants to shut women out, rather the opposite. It wants to give them a chance to do what they want and try their best at it. Just like I did.
What’s the most important challenge you faced throughout your career?
I faced many challenges and I still do, just like each and every one of us. I think that challenges in our career are necessary and inspiring. They help us to avoid becoming idle, and that’s the most important thing. Data Science, despite being a booming market attracting the attention of many companies, still has quite a few obstacles to overcome: first of all, for the companies, learning to identify talented individuals, attract them and help them to become a positive and productive asset for the business. These tasks aren’t easy because of what we were discussing earlier: up until a few years ago there weren’t any real university courses which offered specializations in Data Science. This is the first real challenge for us Data Scientists: leaving the comfort zone represented by the university and facing the world of work which, despite needing a role like ours more and more often, is going through a phase where everything is extremely new, especially in companies that have a more “traditional” organization. A stronger willpower is needed because competition, which today isn’t very high yet, will explode soon. Businesses also have low knowledge about the positioning of our role inside an organization: for example, I’ve been included in the IoT Ecosystem team, which is a business choice with a reasonable justification, but at the beginning it was difficult to understand why my role had been associated with an area that seemed so far from the quantitative world, at first glance. Soon though, I understood that if we want to start a career in Data Science we need to develop the curiosity to understand the ecosystem around us. I have to thank my manager, Andrea Contri, IoT Ecosystem Director in Haier Europe, who values the role I represent highly and supports me on a daily basis both when issues arise and when we reach small achievements together. The challenges don’t end here: how can the Data Scientist bring the most value to the business? How should their performance and achievements be measured? These are answers I find absolutely necessary. As relatively new figures, we need to establish our space inside a community that doesn’t always understand or accept our role, still too “blurry” to be defined inside a “traditional” organization with specific tasks and responsibilities. We need to personally walk the business through this new journey, supporting the company with our points of strength. Obviously, everything is easier and more enjoyable if you have the right people by your side.
Looking at the future, at the next generations of female mathematicians, engineers and scientists: what is the most precious advice you can give to an aspiring Data Scientist?
I’ve been talking way too much during this interview and I want to finish with a specific advice (my manager Andrea will be very happy about it 😉), which was very important to me in the past and I hope that it will have the same effect on many other aspiring Data Scientists, and not only: let’s never stop!
Giada Fusè is a Data Scientist IoT Ecosystem in Haier Europe, a brand which is the global leader in the electrical appliances market and which has always been implementing a strong development strategy in research and innovation. Haier Europe is currently the fastest and most growing group in Europe, and has been included in the “BrandZ Top 100 Most Valuable Global Brands 2020” ranking as the only member of the “IoT Ecosystem” category.