About

My name is Eleftheria (Ria) Kotti. I have more than 7 years of experience in applying statistical methods and machine learning techniques.

I am currently working as a Data Scientist for Raising IT, an Access company. Raising IT operates in the non-profit / charity sector, aiming to increase their efficiency and help them raise more funds.

In the past, I have also worked at Wayhome and GlaxoSmithCline. At Wayhome, I analysed data relating to the real-estate market in the UK to generate insights for the business and its customers. At GlaxoSmithCline, I worked as Principal Statistician / Data Scientist.

During my time at GSK, I received five awards for my high-quality, innovative and valuable contributions to the team’s and company’s success.

Before that, I completed the requirements for a PhD in Statistical Science and Machine Learning at UCL. I was a member of the Centre for Computational Statistics and Machine Learning (CSML). I performed variable selection via penalization, Machine Learning and Bayesian approaches to build predictive models for improving clinical diagnosis of various types of cancer (binary and multi-class classification studies). Technical expertise includes strong programming skills in different languages and ability to quickly learn new software. I have also more than 7 years of successful experience in developing and delivering statistical training material for statisticians and non-statistician in various topics.

Before joining UCL, I received my master’s degree in ‘Statistics & Mathematical Modelling’, from Aristotle University of Thessaloniki, Greece. I completed my master thesis under the supervision of Prof. George Tsaklidis.

Prior to my master, I studied Mathematics at the Aristotle University of Thessaloniki. The final year I worked by Assistant Prof. Aleka Papadopoulou and Prof. George Tsaklidis. into two different projects.