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Senior Lecturer in Data Science

York St John University
North Yorkshire
1 week ago
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Full time permanent


Location: York


Salary: £48,822 to £59,966 per annum


Introduction to YSJ University


York St John is an ambitious, modern university at the heart of historic York and there has never been a more exciting time to join us.


As one of the fastest growing universities in the UK over recent years, we have a new strategy for the next decade, emphasising our commitment to widening opportunity through the power of education and contributing our talents to creating a fairer world, and a more prosperous region. We are putting inspirational learning and impactful research at the heart of this strategy, recognising our academic expertise as our greatest asset.


The School

York Business School is a dynamic and forward-looking school dedicated to put students at the centre of all we do. The Data Science Degree Apprenticeship sits within the York Business School, with business engagement and partnerships at the heart of the programme. Our strong relationships with employers across a range of industries ensure that our apprenticeship remain relevant, impactful, and industry-aligned.


The Role

We are seeking an enthusiastic, adaptable and motivated individual to join our developing Computing and Data Science team in the York Business School. Successful candidates will be able to contribute to developing and delivering teaching related to the Data Science Degree Apprenticeship and should preferably have expertise in one or more of the following: machine learning, AI, big data analytics or cloud computing. You will hold a relevant PhD, be research active and have an established record of research activity and publications. Relevant industry experience would be an advantage.


Required skills and experience

  • A doctoral degree in Data Science, Computer Science, Statistics, AI, or a closely related discipline
  • Demonstrable experience teaching at the higher education level, ideally with experience in apprenticeship or work-based learning settings
  • Strong technical competence in data science domains (e.g. machine learning, big data analytics, data engineering, programming languages such as Python, R, and SQL)
  • Evidence of research activity and scholarly engagement in data science or a related field, with the potential to contribute to the School’s research portfolio.
  • A commitment to inclusive pedagogy and supporting diverse learner needs

Desirable

  • Fellowship (or eligibility) with the Higher Education Academy (Advance HE)
  • Previous experience leading modules and contributing to curriculum design within data science, analytics, or related fields
  • Experience collaborating with employers, industry partners or stakeholder organisations

Additional Information

For informal enquiries please contact Dr Waseem Ahmad via email at ,


It is anticipated that the selection process will include an interview and presentation. Further details will be provided if you are shortlisted for interview.


This role is eligible for Skilled Worker Visa sponsorship subject to UKVI criteria being fulfilled. Please note that we are currently only able to sponsor individuals who are based overseas at the point of applying. For further information regarding this visa route please visit Skilled Worker visa: Overview - GOV.UK (www.gov.uk).


We offer a range of family friendly and inclusive policies and facilities and welcome applications from individuals from underrepresented backgrounds. As part of our commitment to providing an inclusive working environment, consideration is given to all requests for job share or flexible working arrangements.


This vacancy is scheduled to close on the date indicated at the bottom of this advert, but we may close earlier if we receive a high level of applications.


Application process support

We are keen to support you throughout the recruitment process. Before starting your application please refer to the attached candidate application form guidance below which provides advice about completing the application process.


Closing Date - Tuesday 28 October 2025 at midnight


Provisional Interview Date - Wednesday 12 November 2025


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