Profile

My name is Sophie and I live in Surrey with my family, and rescue cat (called Jess because she looks like Postman Pat’s cat)  I grew up with a love of Lego, puzzles and aeroplanes.  I even started work as an aeronautical engineer before I found out about Bayesian Networks and completely changed the course of my career by completing a part time PhD whilst I worked.  I really love swimming (particularly wild swimming in the summer), puzzle books and walking in the South Downs near to where I live.  I can play the trombone and double bass and as I’m a coeliac am pretty proud of my ability to make gluten free Yorkshire puddings.  All there is left to know is that I prefer coffee over tea, pears over apples and my favourite flower is the tulip.  I also like talking about maths whenever I can including about algorithms  https://listenvypod.com/g/dr-sophie-carr/and about Bayes theoremhttps://kpknudson.com/my-favorite-theorem/2019/11/13/episode-48-sophie-carr

I own a small data science company which employs myself, Sam and Abbie.  We don’t have a company office and are located across the UK but get together whenever we can to talk about our work (we talk each week on Skype but it’s always good to get talk face to face)  I also work in the office in my house http://www.instagram.com/p/B4Rs9QsA2HV/?utm_source=ig_web_button_share_sheet

The Bays Consulting Team Meeting

My work involves computer modelling, usually writing in R or Python generally to develop algorithms that use statistics to analyse data sets.  There are two main areas: understanding what the data is showing and this can be done through looking at ratios, distributions, assessing an hypothesis but often starts with simple summary statistics such as box and whisker plots, the mean, range and visualisations of the data.  The second type is trying to predict what will happens either in the future using both AI techniques such as random forests as well as more traditional techniques you learn at school such as plotting a line of best fit.  One of the areas I’m working on that’s really great is predicting where shellfish come from so we can try to help stop illegal fishing https://ima.org.uk/7170/how-marine-biology-maths-and-chemistry-can-help-sustainable-fishing/

What’s great is that most of my work is with with other companies and that means being a mathematician is really a team type of job.

My day has three parts.  Before my kids get up, I read about what’s going in the areas of maths I’m interested in; what’s happening in the industry I work in and then just reading for pleasure (at the moment I’m reading 21 Lessons for the 21st Century)  I’ll also plan what is happening during the rest of the day.  Then I get the kids up and we go to school.

I get back to my desk about 8:30 and then the technical aspects of work start.  I limit answering emails to a couple of times a day (and not at all on a Friday) so I can focus on the “deep work” – solving the puzzles I’m working on and developing the algorithms.  As I’m often a member of a bigger team, I usually have to have a couple of meetings either on the phone or via Skype/Zoom.  The afternoon finishes at school pick up.  Once all the homeworks are completed and the kids are in bed, I’ll usually do a bit more work, this time focused on writing either for a blog, a presentation or a paper.