Scientist - Analytical Lead

Introduction to role:Are you ready to lead analytical control strategies that accelerate medicines from lab to clinic and beyond? Based in Macclesfield, you will shape how we design, validate and deploy analytical methods that directly determine product robustness, speed to patients and regulatory success. You will serve as the analytical lead for oral solid dosage and/or parenteral products across development phases, partnering closely with formulation, engineering, manufacturing, QA and Regulatory. Your decisions will set the control strategy, streamline clinical supply, and pave the way for commercial readiness. How will you leverage modern data analytics and predictive tools to shorten development cycles and raise confidence in every batch released? Accountabilities:

• Analytical Leadership: Act as the analytical skill lead to secure major drug product deliveries, applying a risk-based, flexible approach to prioritisation and timelines, ensuring focus on the highest-value outcomes.
• Control Strategy Ownership: Define and lead an end-to-end analytical control strategy aligned with CMC guidelines across clinical phases, delivering robust, efficient controls that de-risk programmes and enable confident regulatory interactions.
• Method Development and Lifecycle: Design, develop, validate and transfer analytical methods (HPLC/UPLC, LC-MS, dissolution, impurity profiling), establishing stability-indicating performance and ensuring reproducibility across internal sites and CMOs.
• Product Characterisation and Stability: Lead drug product characterisation and stability programmes to inform formulation choices, specifications, shelf-life and critical quality attribute understanding, translating data into decisive action.
• Regulatory Authoring and Interaction: Author analytical CMC content for IND/IMPD/NDA/MAA, validation reports, method transfers and specifications; anticipate and respond to regulatory queries with clear, evidence-based narratives.
• Cross-Functional Integration: Embed analytical deliverables into project plans with formulators, engineers, manufacturing and external partners; enable seamless tech transfer and scale-up with clear communication to governance bodies.
• Investigation Excellence and Data Integrity: Lead investigations, root cause analyses and data integrity assessments; drive timely corrective and preventive actions and ensure GxP compliance with rigorous study design.
• Digital and Predictive Enablement: Apply modern data analytics, multivariate design and DoE to accelerate method development; champion the practical use of ELN/CDS and statistical tools to make data-driven decisions visible and reusable.
• Progression and Impact: Deliver immediate analytical milestones while shaping best practices, mentoring colleagues and contributing to continuous improvement that supports faster, more sustainable delivery of medicines.
  
  MSc or PhD or equivalent experience in a relevant scientific subject area (Analytical Chemistry, Pharmaceutical Sciences, Biochemistry, Biotechnology or related).
• Experience in pharmaceutical analytical science with current knowledge of regulatory CMC requirements for clinical and/or marketing applications and experience authoring CMC analytical content and responding to regulatory queries.
• Strong proficiency with chromatographic techniques (HPLC/UPLC; LC-MS), dissolution, and complementary methodologies for small and/or large molecules.
• Excellent communication, stakeholder management and influencing skills; ability to operate confidently and collaboratively across global, cross skill environments.
• Demonstrated ability to troubleshoot technical challenges and drive data driven decisions.
• Fundamental digital and data capability relevant to analytical development, including: proficiency with multivariate experimental design and basic DoE concepts for method and process understanding.
• Working knowledge of statistics for analytical science and practical use of common data and workflow tools (e.g., ELN/CDS, and statistical software such as JMP or Minitab) for data analysis and reporting.
Desirable Skills/Experience:
• Experience applying advanced predictive analytics beyond foundational skills (e.g., Bayesian optimisation for robustness tuning, chemometrics for pattern recognition, mechanistic/hybrid models for dissolution or degradation kinetics, advanced statistical methods for specification setting and uncertainty quantification).
• Practical experience with basic scripting in Python/R for data wrangling, visualisation, and deployment of predictive models in an analytical context.