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Marta Portugal

Picture by Lesley Martin, interview Poppy Gerrard-Abbott

Marta Portugal

Senior Data Scientist, Merkle Aquila

My favourite thing is having a super messy data set and trying to figure it all out

What is your background and journey to your role?
I’m from Portugal and went to university in Lisbon to study Applied Mathematics and a Masters in Statistics and Operations Research. This led to me to a graduate programme, which introduced me to commercial analytics. This is when I found out I wanted to work with data for the rest of my life. I am now a senior data scientist at Merkle Aquila in Edinburgh. We work with an incredible amount of companies and clients in pretty much every single industry to help them extract maximum possible value from their data.

What does a typical day at work look like?
It depends a lot – I have lots of different responsibilities. I can be with clients, sitting, writing code one day, and then in meetings with senior stakeholders trying to design strategy and solutions to their problems using data. I also co-ordinate the graduate programme.

What part of your work do you find particularly interesting?
One is personal development, helping people to realise their ambitions, achieve their goals and succeed. The other things is having headphones on and nobody talking to me! I love coding, testing my brain and trying to find answers in the data. My favourite thing is having a super messy data set and trying to figure it all out. Being able to answer questions and provide insights using data is definitely one of the best things about the job!

Is there anything you wish you could do more of in your role?
As I progress, I’d like to be more involved in strategic decisions. It broadens my view of data science. It’s not just sitting down and writing code, although there is so much to discover and learn by doing that and so many ways you can apply different techniques. There is the big problem-solving and human side of it. Lately, I’ve been particularly interested in the ethics side of data science and artificial intelligence. Where do we draw the line?

Do you find data science supportive of women?
I am in a very lucky position. In Merkle Aquila, we have a 50:50 split in our company, and that is increasingly the case. We have a lot of women data scientists and the Head of Analytics is a woman. I also attend and have spoken at a number of data/tech related meet-ups. At these meet-ups there’s usually a very healthy split of male and female speakers and attendants which, in my opinion, also shows that the community is evolving in the right direction!

What challenges remain for women and girls in your field?
It is getting better [but] there are still misconceptions about the roles women should play when they have a more technical job. Just because a woman goes into a tech or data job, does not mean it is as valued, equal and scientific as the roles men are doing. It also depends on the industry, as a data scientist you can pretty much work in any industry that you want to. There are still some industries that are heavily male-dominated which can put women off choosing them when planning their career.

What would you recommend to women and girls who’d like to do what you are doing?
Go to university, study, don’t be afraid. Don’t ever despair, keep going and you’ll find a niche you love.

Do you have any favourite data sets or analysis techniques?
There are a lot of advances right now in the field, especially around artificial intelligence, so it’s a fantastic time to be involved. What is really innovative is work on applying the results of research to a commercial context, which is what I’ve focused on for the last few months.

Do you have a hero or heroine?
I’m going to have to go cheeky on this one and say my mum. She is a super woman who raised three kids and taught us that we could be whatever we wanted to.

Do you have a fun fact about yourself?
Don’t know if this qualifies as fun or if it’s just weird, but I can’t eat spicy food, at all! People tend to assume that, being from a Latin country I’d be used to it, but no!