School of Computing, Engineering and Physical Sciences in Partnership with Key Facilities Management

Data Scientist -KTP Associate

REQ000731

Salary Up to £33,500 per annum, plus £6,000 personal development budget

Based at Key Facilities Management Doune, with occasional travel to Paisley

Fixed Term 36 Months

An exciting opportunity for a Data Scientist has become available to work on a Knowledge Transfer Partnership (KTP) to deliver a worlds’ first digital framework for integrated True and automated Facilities Management (FM) capable of autonomous operations, nanosecond procurement, asset monitoring and workplace optimisation; all delivered via a user-friendly application that provides deep insight and integration across multiple FM systems and platforms.

The successful candidate will have the opportunity to register free of charge for a Higher Degree (PhD), receive training in Chartered Management Institute (level 5), work with senior company management to realise benefits to the business and apply their degree and lead their own project in a business environment.

KEY is a sector pioneer having contributed more pro rata to the professionalization of the sector than any other business globally, the business specialises in FM consultancy, tailoring True FM services, digital transformation services and, smart technologies. 

Find out more by visiting: https://key.fm/about-key-facilities-management-consultancy/true-fm/

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. Please visit: www.ktpws.org.uk or contact Stuart McKay (stuart.mckay@uws.ac.uk)

The successful candidate must possess:

A minimum of 2:1 in MSc in Computer/ Data Science, Electronic Engineering or minimum 2:1 BSc. Engineering/ Computing and having equivalent research and development experience.

Application Requirements:

Essential Experience we require as a minimum:

Experience in development and application of Machine Learning and Artificial Intelligence algorithms.

High level Python, C/C++, MATLAB programming experience.

Experience of software design, documentation and management and, using analytics engines for Big data processing.

Essential skills we require as a minimum:

Machine Learning Libraries

Sound working knowledge of numerical and analytical techniques.

Expertise in services and data integration approaches and framework.

Knowledge and understanding of Deep Learning and fuzzy logic systems.

Ability to analyse, design, develop, and validate integrated data science pipelines in varied and diverse business context

Understanding of tagging conventions and taxonomies for equipment and operational data produced by smart devices (Project Haystack, BRICKS)

Ability to work with real-time data from sensors and IoT Platform.

Understanding of Agile software development practices.

If you have questions about this vacancy contact: Dr Ashwini Konanahalli ashwini.konanahalli@uws.ac.uk or Dr Zeeshan Pervez Zeeshan.pervez@uws.ac.uk

Further information, including details of how to apply is available at http://www.uws.ac.uk/about-uws/jobs

Closing date: Wednesday 1^st May 2019

Interviews to be held: Thursday 16^th May at KEY FM Office, Doune.

UWS is committed to equality and diversity and welcomes applications from underrepresented groups.

UWS is a “Disability Confident” employer.

University of the West of Scotland is a registered Scottish charity, no. SC002520