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Business Intelligence Analyst

Do you have strong analytical skills and a questioning nature?  Are you experienced in drawing insight from data and passionate about using data visualisation to support evidence-based decision making?

Based within Strategy and Planning, you will work alongside colleagues to develop and deliver our business intelligence reporting commitments. The Business Intelligence and Data Analytics team provide high quality data visualisations and analysis to help answer key institutional questions and enable evidence-based decision making.  This involves working across the student education lifecycle, research and innovation, and other priority areas.

This is an exciting opportunity for a self-motivated, proactive individual with strong analytical skills and a questioning nature to become part of a key central support service. 

You will be highly competent in handling and manipulating data to produce high quality analyses to support business decisions and be able to communicate findings to a range of stakeholders.  You will have a proven track record of delivering practical results, problem solving and be able to work under pressure. Possessing strong organisational skills, you will also be able prioritise workloads and work to tight deadlines.

You will be self-directing but also work as part of a team and with colleagues across the University.  The nature of the role means that there will be a requirement for very occasional weekend and/or evening working.

To explore the post further or for any queries you may have, please contact:

Alistair Knock, Head of Business Intelligence and Data Analytics

Tel: +44 (0) 113 343 0850, email: a.knock@leeds.ac.uk


Location:  Leeds - Main Campus
Faculty/Service:  Professional Services
School/Institute:  Strategy & Planning Office
Category:  Administrative and Clerical Support
Grade:  Grade 6
Salary:  £27,511 to £32,817 p.a.
Post Type:  Full Time
Contract Type:  Fixed Term (until January 2021 to cover maternity leave)
Release Date:  Thursday 28 November 2019
Closing Date:  Tuesday 10 December 2019
Interview Date:  Tuesday 17 December 2019
Reference:  CSSPO1072
Downloads:  Candidate Brief  
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