Dr. Christopher Dillon

Defined and built the data strategy, infrastructure, and team for a group of 18 businesses. Formed the global data team — owning the full stack from data warehousing and ETL through to executive dashboards and advanced analytics.

• Business impact: +25% OTIF across the group; identified £Xm (figure withheld) in excess & obsolete inventory; recovered ~1% of revenue previously lost to out-of-stock.
• Team: Built and lead a team of PhD-level data scientists and engineers supporting senior leadership across the group.
• Infrastructure: Replaced fragmented legacy reporting with a single Streamlit stack (Entra SSO) serving strategic KPIs down to operational detail.
• KPI strategy: Designed and rolled out EOS L10 scorecards across all departments.
• Advanced analytics: Customer segmentation, margin optimisation, strategic growth initiatives.

Built the data function from scratch for 5 European businesses across tattoo, beauty, and pet grooming supply. Consolidated fragmented data sources into a unified data warehouse, enabling consistent automated reporting across all entities. This work laid the groundwork for the global structure I now lead, and resulted in my promotion to Global Lead Data Scientist.

Established the Data Science function from scratch at one of the world's largest pet-grooming supply companies. Created unified reporting across Christies and sister company Transgroom. Promoted to European Data Scientist as the business was acquired into Nexus Brands Group.

Developed bespoke image feature recognition software for biochip designs. Created technical documentation and presentations for biomedical colleagues.

PhD project: Observations and Modelling of Intensity Time series for Biomedical and Astrophysical Applications — joint venture between Queen's and Randox. Developed statistical techniques for below-noise-floor signals, applied to both stellar lightcurves and biochip diagnostics. Led to novel discoveries of stellar nanoflares (published in ApJ) and to image feature recognition software now embedded in Randox's biochip pipeline — 98.8% reduction in downstream processing time in a $12B diagnostics market. Primarily IDL and Python. Redacted thesis.

Led a Six Sigma investigation into a manufacturing defect, presenting findings to management.