Camille Baysse (pronounce Baïs) is yet another young woman who is doing a job she'd never even heard of when she was still at school... and for good reason. It didn't exist back in 2003! She's a data scientist with Thales, developing systems that help the military predict when their equipment needs maintenance before it breaks down.

Thales is a French high technology company with 80,000 employees and operations in 68 countries. It serves the aerospace, space, ground transportation, digital identity and security, and defence and security sectors.

When she was at school she wanted to be a midwife. But she failed the exams to get into medical school so fell back onto plan B: do some maths and become a teacher. And then during her Master's course in mathematics “I heard about how developing mathematical models to predict situations was of interest to companies.”

Of such interest that she decided to undertake a doctorate. She discovered that Thales had a programme that allows doctoral students to be salaried if their thesis is on a subject proposed by the company. “It doesn't matter whether the thesis actually comes up with an answer to the question posed,” she explained to me over coffee, “because the crux of the matter is the research itself.” Because she was interested in applying predictive statistics she was immediately interested in working on the company's project to develop predictive maintenance for their thermal cameras (those that allow the military to see in the dark, also known as night-vision cameras. They work by detecting heat, from a human body for example, and show them up as, literally, glowing green in the dark!)

She successfully defended her thesis “Analysis and optimisation of the reliability of an optoelectronic tool equipped with a Health & Usage Monitoring System” on 7 November 2013. If you're interested to find out more you can read a summary (in French) of her thesis here.

So how are mathematics involved, I want to know? “Some of the military products made by Thales are equipped with sensors that take all sorts of measurements and track the small details that alert to the fact that a problem is in the making. And we need to be able to filter out all the 'noise', the unnecessary information, and external factors such as the weather which could indicate that a thermal camera is not functioning properly simply because it was 40ºC and it takes longer to cool down in that heat than when its -5ºC.”

Camille explains that her job, as a data scientist, “is to provide information in such a way as to make that information understandable and actionable upon by the end user.” And, she adds, that “in the defence sector you cannot afford to make a mistake. The results could be disastrous.” 

Whilst she was working on her thesis at the University of Bordeaux, she was only obliged to head north to Thales’s headquarters in Paris once every three months or so. “I'd spent six months with my colleagues before starting my thesis so even though I didn't see them very often, I still felt part of the team,” she explains. And just to keep in touch with her favourite subject “I also gave maths lessons at the university,” she laughs.

Today, she and her husband, who also works for Thales “although that's not how we met”, she smiles, have two children, 30-months and 12-months old. “Fortunately the company is very flexible and if necessary we can work from home and we can use the crèche near the office.” 

She muses that it's a shame that so many secondary schools don't explain to their pupils who are good at maths that there are other careers out there for them apart from becoming teachers. “There are so many jobs that need good mathematicians,” she exclaims “so just hang on in there and something you like will come up,” she counsels to those who have a mathematical bent.