Data Scientist KTP Associate Ref: 43006 (Fixed Term)
Location: Brighton, UK
Hours: Full-time up to a maximum of 1.0 FTE (37.5 hours). Requests for flexible working options will be considered (subject to business need).
Grade 8 starting at £47,389 to £56,535 per annum, pro rata if part-time.
Contract type: Fixed term contract.
About the role
The University of Sussex, in partnership with Custom Pharmaceuticals Ltd (CP), offers an opportunity to develop and embed advanced data analytics and predictive modelling within pharmaceutical product development. This post is fixed term for 30 months and is based primarily at CP Ltd’s offices in Brighton.
CP is a UK-based contract development and manufacturing organisation supporting clients in bringing new medicines to market. The Knowledge Transfer Partnership (KTP) will support CP in establishing new in-house capability in data analytics and quantitative modelling, enabling more systematic and reliable decision‑making across drug product development activities. The role sits at the interface between the company and the University and is central to delivering the objectives of the partnership.
At present, many development decisions rely on expert judgement and manual processes, despite the availability of large volumes of process and formulation data. The project will focus on developing and applying advanced analytical and predictive modelling approaches to improve how this data is analysed and interpreted. Initial work will focus on early‑stage product development case studies, with the aim of reducing trial‑and‑error activity, improving development success rates, and shortening development timelines.
Working closely with academic supervisors at the University of Sussex and multidisciplinary teams across CP, the post holder will follow CP’s New Product Introduction process to review available datasets, assess current analytical capability, and design predictive models to support formulation and process decisions. These models will be applied to optimise development activities and embedded into client‑facing workflows.
A key part of the role is to consolidate the modelling and optimisation capability into outputs that demonstrate value to clients and support the first commercial launch of this new service. The post holder will lead day‑to‑day project activity, report to joint University and company governance structures, and contribute to the transfer of knowledge between academic and industrial partners. The role is expected to support CP’s longer‑term strategy by embedding sustainable capability and enabling the development of new data‑driven services.
About you
The successful candidate will have a strong quantitative background in mathematics, statistics, informatics, or a related discipline, and experience in applying analytical methods to data‑intensive problems. They will typically hold a PhD or master’s degree with industrial experience, with a PhD or equivalent research experience being desirable.
They will have experience in mathematical and statistical modelling, including optimisation and decision‑making under uncertainty, and be proficient in Python and/or R. They will be confident in handling, analysing, and interpreting large datasets, and able to communicate quantitative results clearly to non‑specialist audiences.
They will be able to work independently, manage competing priorities, and meet deadlines, while contributing effectively within multidisciplinary teams. They will have well‑developed organisational and communication skills, and an interest in research dissemination, knowledge exchange, and collaborative working across academic and industrial settings.
Equal Opportunity Employer
The University of Sussex values the diversity of its staff and students, and we welcome applicants from all backgrounds. The University is committed to equality and valuing diversity, and applications are particularly welcomed from women and black and minority ethnic candidates, who are under‑represented in academic posts in Science, Technology, Engineering, Medicine and Mathematics (STEMM) at Sussex.
Visa Sponsorship Queries
This role may be eligible for sponsorship under the Skilled Worker route. The assigned SOC code is 2119 – 'Natural and social science professionals n.e.c.' and the going rate is £41,500. If the successful candidate requires a sponsored visa for this role, they will need to obtain ATAS clearance prior to the employment start date. This post may also be eligible for the Global Talent visa, depending on the individual circumstances of the successful candidate.
Eligibility and Conditions
In principle, previous KTP Associates are not eligible to apply. There are circumstances in which a previous Associate can apply for a new KTP. This must be checked with their previous KTP Adviser.
The University requires that work undertaken for the University is performed in the UK.
Contact
If you are experiencing any issues using our application portal or if you require adjustments to be made to the selection process, please contact us on (01273) 873743 or recruitmentadministration@sussex.ac.uk to discuss your requirements.
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