KTP Associate: Data Science, Machine Learning and Optimisation Specialist

University of Nottingham - Computer Science


Jubilee Campus

Applicants are invited to apply for the above role which is a Knowledge Transfer Partnership (KTP) between the University of Nottingham (School of Computer Science) and Pxtech Ltd. This project will focus on developing predictive and prescriptive analytics capability utilising advanced data analysis, data mining, machine learning, modelling and optimisation techniques to maintain Pxtech’s leading industry position as a Business Intelligence (BI) Solution provider for the retail and hospitality sectors. The successful candidate will design and implement various software modules working in collaboration with other developers at the company while also interacting with the academic team at the University of Nottingham. This is an exciting opportunity for a graduate in Computer Science or related discipline to work in a dynamic commercial environment, with the benefit of access to academic research, supervision, support and advice.

PXtech is an industry leader in the development of web based solutions and Business Intelligence (BI), specialising in providing real time sales and productivity information for the hospitality, retail and charity sectors. PXtech enables store owners the foresight of knowing what is happening in their stores by generating key performance data. This operational data enables business owners to make real time systematic business decisions. Supporting some of the leading brands in their customer base, PXtech’s focus is on technical excellence, comprehensive BI and industry expertise. This has led to PXtech’s solutions playing an essential role in more than 40,000 business locations over six continents on a daily basis.

Candidates to this post should have:

  • A postgraduate degree (PhD or MSc) in any of these areas: operations research, data science, computer science, artificial intelligence or closely related discipline.
  • Knowledge and expertise in at least a subset of the core techniques required in this project: advanced data analysis, data mining, machine learning, modelling and optimisation.
  • Experience in at least a subset of specialised software like: optimisation solvers, Weka, R, Matlab, C#/C++/Java, optimisation libraries.
  • Excellent communication skills and experience in working as part of a team. He/she should also have experience in writing reports and conducting effective bibliographic research.
  • Good knowledge of software development methodologies and some experience developing professional software is also desirable.

An excellent individual training package is available.

This full-time post will be offered on a fixed-term contract for a period of 2 years and 10 months.

Knowledge Transfer Partnerships is a government funded technology transfer initiative that supports partnerships between business and universities, placing graduates on challenging, high profile projects. Further information is available at: www.nottingham.ac.uk/ktp

Informal enquiries may be addressed to Dr Dario Landa-Silva, email: dario.landasilva@nottingham.ac.uk. Please note that applications sent directly to this email address will not be accepted.

The University of Nottingham is an equal opportunities employer and welcomes applications from all sections of the community.

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Midlands of England