Statistical machine learning researcher
I am the head of research at Qlearsite. Together we are bringing the next level of analytics to HR and people data including natural language analysis, predictive modelling and experiment design. We help organisations get more value out of e.g. survey data through intelligent text processing techniques, identify patterns of behaviour that are predictive of future long term absence and design experiments that allow people to quickly understand how to e.g. increase engagement and well-being of their employees.
Before Qlearsite I was a PhD and PostDoc at the Machine Learning Group, University of Cambridge working with Zoubin Ghahramani. My research ultimately focused on the automation of statistical model construction and the rational allocation of computational resources when constructing predictive models. Versions of this automation underpin Qlearsite's products.
Before my PhD I was a management consultant at the Boston Consulting Group and before that I received a B.A. in mathematics and M.Phil in Statistics from the University of Cambridge.
We are thrilled to have been recognised by Gartner for being innovative, impactful and intriguing. Read more on our website.
At Qlearsite, we build software to help organisations get the best from their people. Our software takes an organisation’s employee and business data and enhances it by collecting more and better data. All of that information is then automatically cleaned, organised and analysed to reveal hidden powerful truths and help organisations make better and informed decisions. We call this ‘Organisational Science’.
We're currently looking to hire someone with python, java and web development experience to accelerate our rapid prototyping work. If you're interested please get in touch get in touch.
Model criticism using kernel two sample tests (NIPS), many-to-many entity matching (PAMI) and my PhD thesis.