- Built a streamlined data pipeline for OMICS analysis integrating Python and R, replete with logging, audit trail and centralised database, enabling Target Validation of key molecules and Go/No-go decisions.- built analysis tools and platforms for high resolution MALDI imaging datasets, accelerating R&D of this citing edge technology.- Conceptualising and building AI/ML/GenAI solutions for Pharma drug discovery.- Mentoring and coaching a team of Bioinformaticians, building up organic capacity.

Roles:* Skeptic. Brutal examination and testing of mathematical, statistical and AI ML models to identify and eliminate noise or spurious correlations.* Design thinker. Conducted intensive interviews with clients and end users to identify the jobs-to-be-done and value adding potential. Led to user-centric problem formulation and design.* Fast prototyper. Experience in working with UI and software engineers to do quick iterations. * Experience in multiple roles. As part of an R&D team, did project management and organised analysts from various departments, conducted deep dive analyses and visualisation using Python and Javascript.* Strategic thinking. Aligning projects and developed Apps to the landscape and organisational goals.Domains:* Integrating multi-omic signals to achieve personalised medicine and delivering the product using digital health tech.* Detecting warning signs of severe strains of COVID-19, using epidemiological time series analysis with lag correlation and feature engineering.* Building AI and ML models to uncover how mothers pass on allergic responses to children using real world clinical data (GUSTO cohort)* Connecting how changes in gut microbiome affect the developing child

Roles:* Coach. Ran upskilling courses for 150 staff on Hypothesis Testing for Business Outcomes and introduction to Enterprise Data Infrastructure, resulting in improved performance on a before-and-after knowledge assessment that I designed.* Breaking Silos for Digital Transformation. Brought together analysts from disparate Business Units, resulting in achieving insights into Operations and Baggage through joint data analysis projects.* Business Analyst. Used Design Thinking and engineering problem solving workshops to help Ops and HR functions to define and refine their problem statements, shortening the validation cycle to weeks instead of months.* Design and Data Thinker. When faced with the problem of how to bias Design Thinking to yield more data ideas, redesigned Design Thinking workshop from philosophical fundamentals to produce Data Thinking Workshops, resulting in 80% data ideas that aligned with business goals.* Bridge between Data Science and Business Units. Networked with Business Units and gained enough domain knowledge to insource solutions from the Data Science team, resulting in successful optimisation of crew leave and completed explorations into fuel efficiency and warehouse optimisation.* Agile Builder. Quickly learning the domain knowledge, incorporating many business rules and using agile methods, built in 2 weeks an MVP graph network solution to trace flight delays and in 1 week an automated extraction of baggage delays from legacy systems.* Team Player. Conceived, designed and built from scratch a multiplayer roleplaying, webcam-enabled online “murder mystery night” for team bonding, resulting in a memorable evening for the team during the Circuit Breaker of 2020.

* Developing glycoproteomics, capillary electrophoresis, glycomics technology to address clinical and biopharma problems.* Processing large datasets through pipeline development and coding.* Tasked to analyse 1200 glycan datasets, created a scalable data pipeline in Python and completed analysis and quality checking within 2 days instead of the 2 weeks required by the original method.* Tasked with commercialising our products and algorithms, did own intellectual property research, and identified and filed the critical patentable steps, leading to two patents.* Characterised the site specific glycosylation of immunotherapies, which resulted in successful EMA filings.

* Characterised an anti-glycan monoclonal antibody against ovarian cancer, which allowed management to make an informed pre-clinical decision on the drug's development.* Tasked with discovering the enigmatic non-protein target of a monoclonal antibody, I took the cross-disciplinary approach (incl. cell based assays, flow cytometry, MALDI-TOF mass spectrometry, siRNA), which led me to not only identify but also prove the target in situ by loss-of-binding assay.* Faced with the problem of studying dozens of analytes across 8 datasets with no existing automated tools, created own graphical software using Visual Basic, turning the raw data into a quantitative and information-rich data source.* Wrote and Published work in the prestigious Journal of Biological Chemistry. http://www.jbc.org/content/292/15/6163

* adapted adherent hybridomas to serum-free media, which improved the purification of monoclonal antibodies targeting lung cancer.* Combined flow cytometry, protein immunoprecipitation and mass spectrometry resulting in identifying the target of a monoclonal antibody.