Graduate Statistician/Mathematical Modeller
Our story began back in 1998 when Mark Dixon, a university statistics lecturer, decided to set up a one-man-band consultancy offering statistical modelling and research services. Featuring near the top of the Yellow Pages listings was a priority at the time and led to Mark opting for the name “Advanced Training and Statistical Services” - or ATASS for short. Increasingly, his love of football led him to take on more and more sports-related work, and by 2001, he and a handful of colleagues were working under the new identity of ATASS Sports.
Fast-forward 21 years, and the company now boasts one of the largest commercial statistical research teams in Europe and is a leader in the field of applying statistical and mathematical modelling to sports. We have created and continue to develop a collection of state-of-the-art models that allow sporting outcomes to be predicted with unparalleled accuracy.
Who we are looking for?
We are seeking highly motivated individuals to join our research team. Successful applicants will work within new and established multi-skilled teams to develop novel statistical and mathematical models with applications to sports analytics, including probabilistic forecasting of future events.
- You should be a recent graduate or currently in the final year of an undergraduate degree in mathematics, statistics, physics, or a closely related subject, expecting to achieve a First or 2:1.
- An ability to solve problems and to quickly learn and apply new mathematical and computational techniques.
- An understanding and appreciation of probability in relation to sporting outcomes.
- Previous experience in programming / computational mathematics (e.g. R, Python, MATLAB).
- A masters-level qualification in mathematics, statistics, physics, or a closely related subject. (Individuals with a PhD-level qualification should apply for our “Research Statistician” role instead.)
- Start date: September 2021
- Assessment days - various dates in May & June 2021 - all virtual via MS Teams