Providingstrategic leadership for clinical data science, bioinformatics, and AI/ML initiatives across the Rare Disease portfolio, ensuring alignment with R&D objectives.

Leadingthe development of Clinical Data Science strategy within Alexion, contributing to the enterprise-wide data science and AI strategy, and contributing to theAlexion Quantitative Sciences strategy.

Buildingand scalinga high-performing cross-functional team spanning AI, bioinformatics, and translational medicine, accelerating study design and data-driven decision-making.

Establishingand coordinatingAI and data governance frameworks aligned with regulatory standards (FDA, 21 CFR Part 11, CDISC, GxP), reducing compliance risk across clinical programs.

Drivingthe integration of clinical, omics, imaging, and commercial data into unified analytical platforms, enabling sophisticated analytics and knowledge generation.

Leadingbiomarker discovery and validation efforts across multi-omics (transcriptomics, proteomics, genomics) to support patient stratification and therapeutic advancement.

Developingand maintainingdata infrastructure — data lakes, knowledge graphs, and wearables pipelines — to create sustainable, scalable capabilities for rare disease research.

Partneringwith translational medicine and clinical teams to design innovative Phase 1/2 proof-of-concept strategies incorporating omics and digital health technologies.

Being responsible for the identification andprioritisationof therapeutic targets through AI-enabled clinical and imaging approaches, advancing candidates to IND.

Championingthe adoption of digital health solutions, including wearables and imaging, as exploratory and registrational endpoints in clinical trials.

Integratingmulti-omics datasets into pharmacokinetic (PK) models, improving prediction accuracyand strengthening dose-response insights for rare disease programs.

ApplyingAI/ML and omics-driven disease clustering to guide indicationprioritisation and drug re purposing opportunities, expanding pipeline value in rare and metabolic diseases.

Servingas a senior leader representingClinical Data Science in internal governance forums and external collaborations, shaping the strategic direction of data-driven rare disease R&D.

Planningand managingcomplex departmental budget, including forecasting for quarterly, annual, and multi-year cycles, and input to the Strategic Planning process.

Leadingportfolio-level data science capacity management for the R&D unit and contributingto or leadingAlexion Quantitative Sciences pivotal initiatives.
 

PhD ormaster’s degree

DataScience, Bioinformatics, Computational Biology, Computer Science, or equivalent  experience

Minimum 10 years of pharmaceutical or biotech experience

Experience inaDataScience, Bioinformatics, or AI/ML function

Minimum 6 years managing direct reports in a global setting

Deepexpertisein AI/ML methods and their application to clinical and translational medicine

Experience integrating multi-omics data (genomics, transcriptomics, proteomics) in drug development

Thorough knowledge of regulatory standards: FDA, 21 CFR Part 11, CDISC,GxP

Demonstrated ability to influence strategically and build cross-functional partnerships

Track recordof leading AI and data governance in regulated pharmaceutical environments

Experience successfully leading global, cross-functional teams

Strong eye for business and experience influencing and managing budgets

Experience with rare disease drug development and patient stratification strategies

Familiarity with knowledge graphs, graph ML, and mechanism-centered disease representation

Experience with wearables, digital biomarkers, and imaging as clinical endpoints

Experience withindicationexpansion and AI-driven drug re-purposing programs

Broad experience across multiple therapeutic areas beyond rare diseases

Experience managing significantorganisationalchange and scaling data science functions