Back to search results

Data Scientist (KTP Associate)

University of Essex - School of Computer Science and Electronic Engineering (CSEE)

Location: London
Salary: £35,000 to £39,000 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 27th September 2021
Closes: 1st November 2021
Job Ref: REQ05181


Knowledge Transfer Partnerships (KTPs) are government-funded collaborations between universities and businesses. In KTPs, academics and company representatives jointly supervise a KTP Associate who is based in the company, with the goal of improving their competitiveness and productivity. KTPs serve to make better use of the knowledge, technology and skills generated by universities, colleges and research organisations.

Further information is available at:


The University of Essex in partnership with Shepherd Compello offers an exciting opportunity for a technical candidate to work in an innovative project in collaboration with academics from the School of Computer Science and Electronic Engineering. The project aims to enhance Shepherd Compello's use of big data, machine learning and system automation to better serve the needs of all of their stakeholders, whilst ensuring they remain innovators in a rapidly changing world.

This post is fixed term for 30 months and is based at one of Shepherd Compello’s London offices.  


The duties of the post will include:

  • Implementing a system which will automate the claim settlement process and produce predictive models for the claim process, for example for the claim frequency and severity
  • Creating a bespoke actuarial pricing model
  • Paper writing and publishing research findings in flagship venues
  • Embedding technology and upskilling company staff
  • Participating in academic and/or industrial conferences and other events, to disseminate and present research outcomes to the wider community
  • Publishing peer-reviewed articles in High Impact Journals in collaboration with Shepherd Compello and academics at the University of Essex


The post holder must have:

  • BSc in Data Science, Mathematics, Computer Sciences or related discipline.
  • MSc and/or PhD in Data Science, Mathematics, Statistics, Actuarial Science, Computer Science or related discipline, or equivalent industry experience.
  • Practical and theoretical knowledge of computational intelligence / machine learning algorithms for predictive modelling and forecasting
  • Processing and aggregation of heterogeneous data streams based on structured and unstructured data
  • Practical and theoretical knowledge of mathematical and stochastic optimisation approaches such as evolutionary algorithms, probabilistic stochastic models specifically Markov decision processes and reinforcement learning algorithms
  • Excellent knowledge of probability/ statistical models
  • Strong knowledge of R and relevant data science/ statistical packages (e.g. caret, h2o, mlr).
  • Strong knowledge of Python and the relevant data science/ statistical Python stack (Numpy, Scikit-learn, SciPy, Xgboost).
  • Excellent communication and interpersonal skills to be able to work collaboratively in a small team.


55 Gracechurch St, London, EC3V 0EE and South Quay Building, 77 Marsh Wall, London, E14 9SH.

Primary location to be confirmed prior to start date.

Please use the 'Apply' button to read further information about this role including the full job description and person specification which outlines the full duties, skills, qualifications and experience needed for this role. You will also find details of how to make your application here.

Our website contains more information about the University of Essex. If you have a disability and would like information in a different format, please telephone (01206) 876559.

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):


Job tools
More jobs from University of Essex

Show all jobs for this employer …

More jobs like this
Join in and follow us

Browser Upgrade Recommended has been optimised for the latest browsers.

For the best user experience, we recommend viewing on one of the following:

Google Chrome Firefox Microsoft Edge