On 8 March we are celebrating the social, economic, cultural and political achievements of women during on International Women’s Day. For this occasion, I caught up with Jaimy van Dijk, one of our youngest female SAS data scientists, who has proven herself to be a true rock star. I asked her about her job, projects she’s involved in and how it is to work in a team as the youngest woman.
Can you briefly introduce yourself?
I’m Jaimy van Dijk, a data scientist at SAS. I studied artificial intelligence at the University of Amsterdam after finishing the computer science bachelor's at the University of Utrecht. I did my minor about game technology. This immediately reveals my biggest hobby: playing video games. I also play the bass guitar, and you can often find me at the cinema in Utrecht where I watch quite a few movies.
Jaimy, can you give us an idea of how you spend a typical week?
Every week is different. It’s one of the things I really love about the job. One week I’m totally engaged in customer meetings, and the other week I’m trying to solve a technical question. The customers I’m involved with are very diverse. I can spend weeks doing a project for a bank followed by an inspiration session at a start-up.
(Total sidetrack starting here 😉) It’s also the charm of working in analytics – it’s applicable in every sector. Despite some people’s best efforts, I’m still not assigned to a specific industry. This very broad focus has its downsides. For example, I don’t have as much business knowledge as one would have working full-time in the energy sector. Nevertheless, by working closely together with the customer, we can translate the data-driven insights to business value.
What kind of analytics projects do you work on?
I work in the Customer Advisory team in the Netherlands. This means that I help new and existing customers of SAS solve their problems using our software. As you may have noticed, this is quite a broad focus, as well. That’s why our team consists of people with different specialisations. My focus is on advanced analytics and open source integration. My favourite projects involve a kind of deep learning. Think of computer vision and reinforcement learning, but I also really like working on automating processes like model validation and model retraining.
How have you seen the teams you are working in evolve over time?
This is actually my first real job. I started right after finishing my master's. I actually heard I got the job a few hours after I had my thesis defence. When I started at SAS, I was the only one in my team under 30. I think a lot of my colleagues also needed to get used to working with me. But looking at my team now, many young people have joined.
What is it like working in a team and being one of the youngest?
What I noticed the most about the age gap is the humour and the way of talking. I can laugh with everybody in my team, but I remember one moment when I just started working here that made me realise how young I was. I was doing the SAS Programming course at my desk, and I was reading about a parameter to show no observations in a procedure. This parameter is called noobs (short for no observations, of course) but what I saw was n00bs, a common term used in gaming to refer to people who suck but act as if they own it. I laughed out loud and looked around me to see if I could share this hilarious finding with somebody, but it was then that I realised that my older colleagues would understand this reference.
I think it’s valuable to work in a team with a lot of age-diversity. We make fun of each other, that’s for sure, but in the end, we are all eager to learn something as well. I really learned a lot from shadowing my colleagues and I use their experience whenever I can. In return I teach them something new as well. In the very first months at SAS I was already doing sessions about Python, convolutional neural networks and general AI presentations for my colleagues. Something I think everybody starting their first job should know is this: just because you don’t have the experience doesn’t mean you don’t bring anything to the table. Don’t be afraid to speak up and share your insights, they will certainly be appreciated.
What is it like working in a team and being a woman?
Answering this question is the most annoying thing about being one of the few women on the team. A friend of mine has the best answer to this question: “I don’t know what it’s like to do what I do as a man, so I cannot answer this question.” Still, I understand where the question is coming from. Do I ever feel as if I’m treated differently? I do sometimes.
As a young woman in a technical, customer-facing role I’m often being asked to present at events or meetings. I’m not sure if I’m being asked because of my knowledge or because they think it “looks better” when a woman is presenting. And sometimes it’s the other way around. I may be presenting something because it’s my expertise, and the customers think I’m just there “to look pretty,” and then I need to convince them that I know what I’m talking about. But then again, I don’t know if my male colleagues face the same sort of thing; maybe I should talk to them about it.
What do you think is key for a great team working with analytics?
In the ideal situation, a team would be as diverse as possible: different ages, different genders, different ethnicities, different socioeconomic backgrounds, different parts of the country, etc. Everyone is biased, and people with different backgrounds can challenge each other’s biases. But putting different people together does not automatically create a good team.
Here is where a good manager comes into play. In a diverse team, you need to create an environment where different points of view are respected and evenly valued. This really is very difficult, and finding the right people to create this environment is even harder. Nevertheless, I have seen that it’s possible, and I want to give a big compliment to my manager, who was able to create an environment where young people are just as valued as the more experienced ones. If we can recreate this for the other dimensions of diversity, we may be very close to creating the ideal team.
What advice would you give to all younger women working in analytics?
I know a lot of women in analytics who see themselves as “one of the guys” and have no gender issues. And this might be true – I never feel like a victim, and my colleagues have never disrespected me in any way. However, I do believe that more diversity does lead to better teams and better solutions. So I want to encourage women to care about this issue so that at some point you don’t have to be “one of the guys” to work in analytics. So do speak up when something may be uncomfortable for you!
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