National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Student Data and Management Information (SDMI) Manager

Courtauld Institute of Art, University of London
London
8 months ago
Applications closed

Related Jobs

View all jobs

Diversity Data Analyst

Data Scientist

Junior Data Analyst at Pion (Remote)

Research Assistant in Data Science

Payroll Data Analyst

Lecturer in Knowledge, Information and Data Science

Job description The Courtauld Institute of Art is the UK’s leading institution for teaching and research into the History of Art and the conservation of paintings, and is also home to one of the finest small art museums in the world. The Courtauld is currently undergoing a capital transformation project that will make The Courtauld’s world-class artworks, research and teaching accessible to more people – in the UK and internationally. Based in the Student and Academic Services (SAS) department and reporting to the Academic Registrar, the role holder is responsible for the preparation of The Courtauld’s student data statutory returns for external agencies, such as the Higher Education Statistics Agency (HESA) and Office for Students (OfS), ensuring their timely and accurate production. The role holder will provide detailed analysis and understanding of the data to enable full reporting to these external agencies to take place. The role holder will be considered an expert SITS user, advising colleagues and identifying developments to processes. The role holder will be responsible for the production of management information in respect of student data and the production of ad hoc reports on student data. The role holder will also have responsibility for the preparation and updating of the academic timetable. You will have: • Comprehensive expert knowledge of Tribal SITS: Vision Student Records System, including HESADOR statutory reporting, Task Management, Batch Processes, Standard Letters (SRL). • Extensive work experience in a HE data analyst/SITS role. • Extensive knowledge of HE statutory returns – HESA Student Record (Data Futures), HESES, Graduate Outcomes. • Experience of developing and managing timetable systems in a HE environment e.g. CELCAT. • Experience of staff management and leading a small team. • Excellent interpersonal skills in order to communicate effectively with staff, students and external bodies. • Excellent attention to detail and able to work effectively and accurately under pressure to tight deadlines. For further information, please see the Job Description and Person Specification. To apply, please complete the online application, which will require you to supply a CV and a supporting statement of up to 1500 words. The supporting statement should set out how you meet the criteria of this position. Please explicitly address the criteria set out in the job description and person specification when preparing your statement. Closing Date: 4th November 2024 Interview Date: Week commencing 18th November 2024 (day to be confirmed) The Courtauld is working towards improving and embedding equality, diversity, inclusion, and anti-racism. From £51,842 per annum including London Allowance

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.