Jennifer Roubaud did not take the traditional route to get into the data industry. She doesn’t have a data science background, nor did she study data science at undergrad or post-grad level. But she has always been curious about and had an interest in the sector. So, she decided to see what transferable skills she had that could serve her in her ideal industry.
“For me, it was my strategic and management skills and that’s how I ended up going into collaborative data science platform Dataiku as a manager of a team,” she told DataIQ. Now, she is surrounded now by data scientists, sales people, engineers, architects, technical people and those who work on the customer side, all of whom are experts in what they do. For her, this creates a very exciting environment to work in, where she also constantly learning while doing her job.
She explained that her role is to head up the entire team in the UK and Ireland and take responsibility for setting up the objectives and the vision, planning how those will be executed and then making sure that happens. She also described the role of Dataiku in the UK’s data science ecosystem as that of being an advisor to companies that are aware they need to start implementing data and analytics and are seeking help in doing so.
"What organisations are really looking for is smart, business-minded people that can use data."
Roubaud sees this path of into the data science industry from a non-scientific background as becoming more common, saying there is a trend in the industry of not trying to bring in only experts to do data science. “Most organisations are equipping themselves with platforms, with tools to skill up their employees and what they are really looking for is smart, business-minded people that can use data to provide more creative and innovative solutions to real-world problems,” she said.
Roubaud added that, as data scientists might lack grounding in the real world and not have a full understanding of the ins and outs of the business side, the two types of data professionals form an complementary working relationship.
She has no doubt that there is a deficit of women in the industry, quoting a Forbes statistic that only 26% of people working in data are female, and sees this trend of recruiting smart people, rather than just data science experts, as a way of getting more women into the industry.
"Even if you don't have this data background, organisations will want to hire you and train you."
“Nowadays, most of the tools and platforms are evolving in a way that, even if you don’t have this data background, organisations will want to hire you and train you while you are an employee,” said Roubaud, who talked to attendees at the DataIQ Future 2017 conference about becoming a large-scale data innovator. In fact, Dataiku is also looking for smart, curious people of any gender to join her company, highlighting the recent promotion of one of its “most brilliant data scientists” who is female to a team leader position.
Roubaud also gave the example of one of Dataiku’s clients. CPG is taking people on from university and even high school, as long as they are smart and like to solve problems. As a result, there are now more women than men working in the data science team. “They give them the tools to help them work on analytics projects without knowing how to code and it’s not a problem,” she said.
She recognised there is a commonly-held stereotype that women are more collaborative and communicative than men. While not wanting to generalise and say whether this is true or not, she did say that the industry itself is going in that direction.
“I would say that the industry needs people whether they are expert or not. Some of the key qualities that are stereotyped of what women do are actually things that are needed for the industry and that men and women both need to be focused on,” she said.
Roubaud has observed this shift despite being relatively new to the data industry, having pivoted her career from consulting to data following the completion of an MBA in 2016.
“After many years in consulting, I did some corporate development where you do a lot of data-driven research. I went to Columbia Business School and it was the opportunity to hit the reset button,” she said.
"What I like about data is it has no bias."
She chose to move into the data industry because it was still emerging and provided the opportunity to have an impact on the future. She said: “It is still quite a small world, at least in the UK. When you are part of the ecosystem, it feels like family. And it open doors for organisations we work with to give a better service, better understand their customers, do better prevention and better help people. I really like what that means and the potential and power that it has.”
Roubaud’s experiences have led her to believe that the data industry can be a level playing field. “What I like about data is it has no bias. You let the metrics talk and tell you what is happening and what could potentially happen. That is something that I like,” she mused.