Multi-omics analytics, bioinformatics workflows, systems biology and modelling, pharma R&D digital transformation, and business analysis & product ownership for scientific platforms. Each area ends with where I've actually done it.
High-throughput sequencing and omics technologies to understand biological systems, identify disease mechanisms, and generate testable hypotheses, across the full analytical lifecycle, from experimental design and QC through statistical analysis and biological interpretation.
Scalable bioinformatics workflows for reproducible analysis of large-scale biological data, designing, implementing, validating, and documenting pipelines so they remain repeatable, maintainable, and deployable across research teams and computing environments.
Computational models of how biological behaviour emerges from interactions between genes, proteins, pathways, and cells, moving beyond descriptive analysis to investigate mechanism.
Helping pharmaceutical organisations assess and improve how scientific data, workflows, and laboratory operations support research productivity, including how digital technologies can accelerate drug discovery through better data accessibility, workflow efficiency, and scientific collaboration.
Translating scientific stakeholder needs into user stories and technical requirements for engineering teams building scientific-data platforms. Working as the life-sciences domain SME inside a cross-functional product team.