The University of London
The University of London is the UK’s largest provider of international distance and online learning and the convenor of a federation of 17 London-based universities, many of which are among the highest-ranking universities in the world.
Collectively the federation represents a cohort of some 250,000 learners and 50,000 academic and professional services staff. Within this cohort are around 40,000 University of London students who study programmes which are developed and delivered in partnership with our 17 federation members.
The University of London is also home to the School of Advanced Study, the national centre for the humanities and a champion for the arts and humanities.
Although proudly rooted in London, our community and impact are global.
Our passion for increasing access to education and mobilising the collective power and expertise of the federation is central to our ability to transform lives around the world and address the global challenges of the future
The Role
The University of London is accepting applications for Online Tutors with a specialist background in Financial Markets to support the online MSc Data Science programme, with academic direction from Goldsmiths.
We are looking for enthusiastic and motivated individuals with experience in higher education and distance learning. In particular, applicants will need to have extensive experience of undertaking assessment duties similar to those outlined in the role description.
The Online Tutor’s tasks include proactive support to students via the Virtual Learning Environment; marking summative assessments and providing detailed feedback. Each Online Tutor will be supported by a Module Leader and Programme Director, and will work closely with University of London’s Programme Manager.
More information about the MSc Data Science programme can be found here:
Module Specification
As an Online Tutor, you will be required to provide academic support for the following module on the MSc Data Science programme:
Financial Markets
As a brief overview, this module will guide students use mathematical and computational approach to understand how financial markets work well enough to analyse, evaluate and implement investment decisions involving financial instruments.
Location: Remote
Employment Type: Self-employed contractor
Salary: £1,451.89.00 flat fee per study session
Assessment marking is paid separately at £24.53 per coursework assignment and £13.58 per exam script marked.
Candidate Profile
You will be a motivated individual who enjoys working with students and who is driven to support students to achieve success in their studies.
You will have experience working in a Higher Education Institution and have a data science or related qualification at Postgraduate level.
For a full role profile, please refer to the job description below.
Further Information
To be considered for this opportunity, please submit your Covering Letter and CV (by clicking ‘apply for job’ at the bottom of this page) before the closing date at midnight on the 18th of February 2026.
As part of our recruitment process, we require professional references to verify your qualifications, work experience, and performance. Please be prepared to provide a list of references, including at least two individuals who can speak to your professional skills and accomplishments.
The University will be unable to sponsor candidates for a visa for this role. and cannot consider applications from individuals currently on a student visa.
The University reserves the right to close the vacancy earlier than the published end date should it receive sufficient applications to warrant earlier shortlisting.
If you have any queries in relation to this opportunity, please contact the Online Tutor Network team via on tutor.support@london.ac.uk
The University of London is committed to promoting a diverse and inclusive working environment where we can all be ourselves and succeed. We particularly encourage applications from members of Black, Asian, and Minority Ethnic communities as this group is currently under-represented at all levels within the University. All appointments will be made on merit, based on the criteria named in the job description.
Pursuing excellence in education and equal opportunities.