Women in data: Interview with a Data Scientist at Kantar

Article written by Jacob Knight, Head of Data of X4 Technology.

As developments in machine learning, tooling and applications continue to become more sophisticated, it’s unsurprising to learn that more companies are planning to grow their data science teams.

A recent survey found that in 2018, 18% of companies employed 11+ data scientists with that rising to 39% in 2020. The same survey found that companies with 1,000+ data scientists, increased from 1% in 2018 to 3% in 2020, which highlights a small but significant growth in larger organisations.

As more companies look to increase the number of data scientist they hire, it’s important to recognise that male analysts and data scientists outnumber females 4 to 1. In an industry that seeks to understand and influence the lives of many, diversity across the workforce is something the industry is striving for.

I spoke to Laura Palacio García, a data scientist at Kantar to find out about her journey into data, her thoughts on attracting and retaining females in the industry and also, what she’s most excited about when it comes to future developments in data science.

What interested you to start a career in data science?

I started becoming interested in data science in university when I had some assignments that involved programming and plotting data showing the results. I thought it was so exciting how I could make a computer do all of that and I had so much fun in the process of building the algorithm. That is when I decided that I wanted to know more about how to explore data in such a way.

What are the most prominent challenges faced by a data scientist in the wake of Covid-19?

I believe that we are quite lucky in the sense that our work enables us to work from home quite easily and I think that made data scientists not be as affected by redundancies as other positions. Also, the fact that data scientists are needed in a lot of different industries gives you the ability to switch industries easier. I have a lot of data scientist friends that actually found new jobs in the peak of lockdown.

As few as 15% of data scientists are female, do you feel the industry is making strides to attract and retain more female talent? If yes, how?

It is a shame to hear such low numbers and I am not sure what the best solution to solve that would be. I know that it all starts when we are younger and that is why some organizations that encourage girls to code from a young age are so important.

We must make sure girls know that coding is a possible career path for and it is not only meant for the stereotypical computer scientist. However, I do believe that now some data science teams in different companies are trying to have a more diverse team with people from different backgrounds and genders, and I think that is a great thing to do, but I believe we are still far away in terms of an equal representation in data science. Hopefully, in the years to come, more and more girls will be encouraged to study more STEM degrees and will choose data science as a career path.

“Data science has an image problem.” This has been said a lot in the news recently, what would be your advice to employers who want to change this perception and create a more inclusive culture in their business?

It is true. Like I said, data science and software development in general is associated to the stereotypical “nerdy” computer scientist male and it is a shame to know that maybe that is the reason why so many females are not considering this career path (unconsciously). I am quite a social person and I have received a few comments along the lines “you are not the typical coder”, etc.

My advice to employers that want to change that is to make sure their team is very social and do fun activities and collaborate with other teams in the same company. In my personal experience, all of this has made me more excited about a new role. I do not want to sit in a development team only with my laptop without interacting with anyone else from the business. The social side is as important as the actual work and this might help change this “nerdy” stereotype of computer scientists.

What excites you most about recent developments and the future of data science?

I believe there are two very exciting things in the data science field happening right now.

AI is the most exciting part about data science in general, although I believe there is still so much to learn about what happens behind all of that. I read somewhere that half of the data scientists working on an AI project don’t really know what goes on during the training of the algorithm since the computer learns on its own without anyone really controlling it. The second most exciting development is the increase in the computer power we have nowadays. It is growing exponentially year by year and it will allow us to perform incredible tasks and process a lot of data in a really short time and that is what will change the future.

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