Data Scientist KTP Associate (UK Sponsorship)

Uk
May 6, 2026

Job Description

About the Opportunity

The University of Sussex, in collaboration with Custom Pharmaceuticals Ltd (CP), is offering an exciting Knowledge Transfer Partnership (KTP) opportunity focused on advancing data-driven pharmaceutical development.

This role sits at the intersection of academia and industry and is based primarily at CP’s Brighton site. The associate will play a central role in building and embedding advanced data analytics, machine learning, and predictive modelling capabilities into real-world drug development workflows.

The partnership aims to transform how pharmaceutical development decisions are made by shifting from largely experience-based judgment to evidence-driven, data-optimised decision systems.

You can learn more about KTP programmes via official UK Government resources:

Role Purpose

The appointed Data Scientist will:

  • Develop and implement predictive modelling and optimisation tools for pharmaceutical product development
    Analyse complex, multi-source datasets to improve formulation and process decisions
    Translate raw experimental and operational data into actionable insights for industry use
    Reduce reliance on trial-and-error approaches by introducing structured analytical frameworks
    Support the design of data-driven decision-making systems within CP’s New Product Introduction pipeline
    Help embed analytics capability into long-term commercial operations and client services
    Contribute to knowledge transfer between academic researchers and industrial teams

The role will also involve producing outputs that demonstrate measurable value, including early-stage case studies and models supporting real product development cycles.

About You

The ideal candidate will bring strong quantitative and analytical expertise, along with a collaborative and industry-focused mindset.

You should have:

  • A background in data science, mathematics, statistics, computer science, or a related discipline
    Experience in machine learning, statistical modelling, or optimisation techniques
    Strong programming skills in Python and/or R
    Confidence working with large, complex datasets
    Ability to translate technical findings into clear insights for non-technical stakeholders
    Experience working in cross-disciplinary or applied research environments (academic or industrial)

Desirable attributes include:

  • PhD or equivalent research/industrial experience
    Familiarity with pharmaceutical, healthcare, or process industries
    Experience delivering data-driven business or operational solutions

About the Partnership Environment

This role is part of a Knowledge Transfer Partnership (KTP), a UK Government-backed initiative designed to embed academic expertise directly into industry.

The associate will benefit from:

  • Joint supervision from University of Sussex academics and industry mentors
    Professional development training and leadership support
    Exposure to strategic industrial decision-making
    A structured pathway for career development in applied data science

Working Environment

The University of Sussex is a research-led institution committed to innovation, collaboration, and real-world impact. The School involved in this project promotes:

  • High-impact interdisciplinary research
    Strong engagement with industry and healthcare sectors
    A supportive and inclusive research culture
    Opportunities for international collaboration

The campus is located near the South Downs National Park, with excellent transport links including Falmer train station and cycling infrastructure.

Equality, Diversity & Inclusion

The University actively promotes inclusive recruitment and encourages applications from underrepresented groups in STEM fields. Support for flexible working and accessibility adjustments is available throughout the recruitment process.

Useful UK equality and workforce guidance:

Additional Information

This post is fixed-term and aligned with KTP funding conditions
UK work eligibility and visa sponsorship may apply depending on SOC code and individual circumstances
The role is based in the UK and requires on-site engagement with industry partners