CRANFIELD UNIVERSITY

Data Scientist - Product-Service Systems Optimisation (KTP Associate)

4 days left

Location
Cranfield, United Kingdom
Salary
£30,000 to £35,000 per annum
Posted
17 May 2019
End of advertisement period
30 Jun 2019
Ref
3053
Contract Type
Fixed Term
Hours
Full Time

School/Department School of Aerospace, Transport and Manufacturing
Based at Off Campus
Hours of work 37 hours per week, normally worked Monday to Friday
Contract type Fixed term contract
Fixed Term Period 36 Months
Salary £30,000 to £35,000 per annum
Apply by 30/06/2019  

Role Description

An exciting opportunity has arisen to work as a Knowledge Transfer Partnership (KTP) Associate on a 36-months collaborative project between Siemens Industrial Turbomachinery Ltd. (SIT) and Cranfield University. This project aims to allow SIT to embed a novel toolkit that will optimise service oriented solutions and offer clients a number of new ways of working together. The project will transform the way SIT undertake business with clients. You will also enjoy a personal £6,000 development budget.

SIT designs, manufactures and services small industrial gas turbines (5 - 15 MW over 4 main types of turbines). Globally SIT have an installed fleet of over 3,000 units across over 90 countries with >1,700 of these in operation. Cranfield University is an exclusively postgraduate university that is a global leader for education and transformational research in technology and management. Cranfield Manufacturing is one of the major themes at Cranfield University. Our capability is world-leading and combines a multi-disciplinary approach that integrates design, technology and management expertise.

As a KTP Associate, you will be based at Siemens Industrial Turbomachinery Ltd. in Lincoln, and will work closely with the academic team at the Cranfield Through-life Engineering Services (TES) Centre, which is part of the School of Aerospace, Transport and Manufacturing (SATM).

The KTP project will focus on transforming the business model for providing after-sales support and services. SIT needs to develop a mathematical approach in the form of a novel toolkit to assess, quantify and compare tailored business model solutions to offer clients a solution that suits them and derives financial benefit for us. The toolkit would optimise the internal and external supply and demand to deliver multiple different business model solutions at any given time. With >600 customers, in 90 countries, managing a portfolio of more than 3,000 turbines, with >40,000 parts, and >800 suppliers as part of our supply network this is a significant challenge. This would take into account the client type and SIT resources needed to maximise the effectiveness at deploying turbines and, ultimately, the productivity and profitability.

We are seeking a highly motivated individual with a postgraduate degree (MSc and/or PhD) and a First degree (First or 2:1) in Engineering, Business studies or a related area.  You will have experience in optimisation and any of product service systems, and servitisation and in software tool development.  You will have knowledge of different simulation and optimisation methods and tools. It would be advantageous to have a good level of experience in programming language.  You will have strong oral, visual and written communication skills, and presentation skills, and be able to work as part of a team. 

This partnership received financial support from the Knowledge Transfer Partnerships (KTP) programme. KTP aims to help businesses to improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK knowledge base. This successful Knowledge Transfer Partnership project, funded by UK Research and Innovation through Innovate UK, is part of the government’s Industrial Strategy.

At Cranfield, we value Diversity and Inclusion, and aim to create and maintain a culture in which everyone can work and study together harmoniously with dignity and respect and realise their full potential. We actively consider flexible working options such as part-time, compressed or flexible hours and/or an element of homeworking, and commit to exploring the possibilities for each role.