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The Data Scientist

Age: 35 | Location: London, UK


There’s a rabbit on my screen, stretched out along the bottom of a radiator underneath the window. She’s called Marshmellow. It was supposed to be 'Marshmallow', apparently, but The Data Scientist spelled her name wrong on a form at the vet once.


‘She's lovely, but she gets really hungry in the morning and does come along and headbutt you if you haven't fed her.'


The Data Scientist isn't a fan of all animals though. Fish terrify her.


‘I remember I was in Cuba and I was telling a girl I was travelling with at the time that I have a big phobia of fish, and then the next thing I know a fisherman just flopped a massive fish, closest thing to a salmon, on the floor. It was there flapping on the pavement and I screamed and ran.'


'Someone told me that piranhas can stay alive thirty minutes outside of water. So gross. It’s horrible.’

I ask her if she can eat fish, or if even that is too scary.


‘I don't really eat it. I don't like the smell either. I'll have prawns if there’s no heads on them, like the little tiger ones in a curry can be quite nice, or calamari if it's not too fishy, but everything else no. And I know they’re really good for you! Loads of people love fish! I’m just not a fish person.’


It’s actually lunchtime. We’re chatting during the short break The Data Scientist has between meetings. She is sat at her desk in a black short-sleeved top. Her long hair is a loud auburn colour, but she insists it's the best thing about her and that she’s never considered dying it.


‘People see me before they hear me. I often get flagged in London, people like, oh good, you're here. It used to be much more red, but with red hair you age gracefully, it fades slowly, so now it kind of feels more brown sometimes.’


She comes from a trio of redheads; her mum and her younger sister have red hair too.

Her older sister is a brunette, but the pair of them have something else in common.


‘She's one of the smartest, toughest cookies that I know. You don't realise at the time, when you're little, but there is a natural role model in your life and I have to say mine was my older sister. I'm not picking favourites, because I have a younger sister who's fabulous as well, but when someone's older than you, you can learn and develop by seeing them progress.’


The three of them grew up in Ireland, in Portlaoise, about an hour outside of Dublin.


‘I grew up next to a bog and, like, cows were in the field beside me. I'm a complete country bumpkin. You can take the girl out of the country but you can't take the country out the girl. I have barrels of hay and sawdust being delivered today. For that fluffy thing.’


She points at Marshmellow, who is still lying in the same spot under the radiator, ears by her sides.


However, for the last twelve years, The Data Scientist has lived in London. She loves it there, and now has no desire to live anywhere else.


‘I’m walking distance from the Tate Modern. I'm a big fan of art and just love the Tate and the National Gallery. London has that artistic culture, but it's also multicultural. Sometimes in the summer it's really hot and I hear Spanish accents or Portuguese accents and I feel like I'm in South America. I just love London.’


She's made herself part of the local community too, joining all sorts of clubs and taking up all sorts of hobbies.


‘I've been playing chess with my local chess club. And it's really nice because they're lovely people. They play every Sunday, but the thing is a lot of them are grandmasters. If you play with them they just wipe the board within a couple of moves and you're done. It's fascinating. But you learn from them and I absolutely love that.’


When she’s not playing chess, she takes Brazilian jujitsu classes.


‘I'd really love to get my blue belt.’

At work on the other hand, it’s all about numbers. I suggest that this quite a rigid and formulaic job to have, then The Data Scientist lets me in on a secret: it’s much more variable than people would expect.


‘Even though it's coding and it's logical, and the algorithms are very black and white and clear cut, data science isn't an exact science. It's a lot of exploring. Sometimes things work, sometimes things don't work. It is very dependent on the data and if the data is changing every second, minute, hour, week, month, it’s difficult.’


What’s particularly interesting is that although she has had great success in her field, an ambassador of young women in science, she almost never became a scientist. Her sliding doors moment happened when she was applying to universities in her final year of school.


‘My whole vision was to go to that university in that place. And I chickened out last minute because my boyfriend was in university already. Just before the deadline, I changed school to be with him.’


Little did she know at the time, this was a decision which completely changed the course of her life.


‘I wanted to transfer to the uni I was originally meant to go to. I was hoping to go to Galway which was more chilled. But I'd made good friends, a sound network, and my professors didn't want me to move. They were like: you are one of our top students, you get all As, we’ve very little women, and we don't want you to go.'


'The nice thing that happened out of that was that I had never studied science - I went to study maths and statistics - but because I wanted to transfer, they were like, 'what if we give you a spot in mathematical science' and I was like 'I actually never studied science, I don't meet the criteria.' But they let me take a spot, as long as I did one module in science.'

'So I have a degree in science, but I've never actually properly studied physics, biology, or chemistry and I couldn’t tell you much about it.’

I ask if she has any regrets. She tells me she has none at all.


‘I ended up in quite a good spot. I don’t think I ever would have gotten a degree in science if I hadn’t been led by love.’


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