Data Scientist KTP Associate

Hours: Full-time considered up to a maximum of 1.0 FTE / 37.5 hours per week.

Contract Type: Fixed term for 24 months

Expected Interview date: 10 June 2026

Expected start date: August 2026 

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 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 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.

About our Division

Please find further information regarding the School of Mathematical and Physical Sciences.

The School of Mathematical and Physical Sciences is proud to hold a Bronze Athena Swan Award.

Why work here

Find out more about our reward and benefits package.

Find out about our equality, diversity and inclusion

Further Key Information

Please contact Ivor Simpson (I.Simpson@sussex.ac.uk), Marianna Cerasuolo (M.Cerasuolo@sussex.ac.uk),
or Archie Kubba (a.kubba@sussex.ac.uk) for informal enquiries.

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