13 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"M.V" positions at Oxford Brookes University
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experience in a post within an information and advice/guidance setting Experience providing information, advice and guidance services; consistently providing excellent customer service through multiple
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of working autonomously and handling sensitive corporate information; Excellent and sensitive communication and interpersonal skills; A flexible “can do” attitude to work. Problem solving and negotiation
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information; Excellent and sensitive communication and interpersonal skills; A flexible “can do” attitude to work. Problem solving and negotiation skills; Excellent organisational, time management and
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design principles to remain fit for purpose. Data-Driven Insights: Utilise people metrics and data to identify trends and design solutions for improvements in areas such as sickness absence, NSS outcomes
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programmes aligned with our targeting criteria ● Evaluate outreach activities, analyse data, and produce reports with recommendations for improvement ● Organise large-scale inbound and outbound events
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-ordinating project activities, researching good practice, analysing and interpreting data, or writing a report. The projects we deliver are diverse and interesting, and colleagues work on a variety of projects
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sessions. You will need to be competent at learning and using IT and data systems. The role includes using timetabling software and the Service Now IT ticket system to help organise the Academic Advising
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planning and execution of targeted recruitment initiatives to meet recruitment targets Undertake research and data analysis to identify emerging business opportunities and contribute to the validation and
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project management Excellent teamworking, IT and communication skills. For more information please see the attached job description and person specification. Equality, diversity and inclusion At Oxford
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learning is solely interested in model selection (i.e., identifying, given the available data for the task at hand, the model that is expected to perform best), we propose a new paradigm for an