New KTP Vacancy : Senior Data Scientist
Latest Knowledge Transfer Partnership associate vacancy.
An exciting opportunity to be part of a Knowledge Transfer Partnership (KTP) between the University of Reading and Focaldata Ltd.   The 24 month fixed term contract is to research and apply the latest computational methods in Bayesian statistics to build a state of the art data analytics pipeline, enabling a new type of market research company to be built.
About Focaldata: 
We came together united around a simple mission; that critical decisions, be that in government or business, should be driven by accurate and reliable information.  We were shocked that some of the most important decisions our leaders had ever taken were based on an erroneous understanding of public opinion. And the problems weren’t just in politics, they were everywhere.
Even more frustratingly, the AI revolution had given us the tools to get more accurate predictions than traditional survey methods.
Coming from Entrepreneur First, Google, and Cambridge and Warwick PhDs, we decided to build a new type of market research company, which applies the latest methods in computational statistics to survey data. We are committed to user-centric software design, and care deeply about our customers and the public.
About KTP:
This position forms part of the Knowledge Transfer Partnership (KTP) funded by Innovate UK.  It’s essential you understand how KTP works with business and the University, and the vital role you will play if you successfully secure a KTP Associate position.
What you will do:
This KTP position offers a unique opportunity to work alongside academics from the University of Reading and Focaldata’s Chief Data Scientist.
You will research how to improve our Bayesian Insight engine, which primarily uses MRP (multilevel regression and poststratification), to estimate public opinion better. This research involves the development of novel methods in Bayesian statistics and machine learning, analysis on various datasets, and implementation of statistical models into production.
The position combines academic research with commercial focus. The candidate is expected to publish papers and also work in a commercial environment with real-world clients.
Find out more by downloading the job description here
To find out more about the Knowledge Transfer Partnerships programme here.