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Dr. Christopher Dillon

Global Lead Data Scientist · Head of Data
Global Lead Data Scientist Jan 2025 - Present
Nexus Brands Group

Defined and built the data strategy, infrastructure, and team for a group of 18 businesses. Co-founded the Global Finance and Data Analytics Department — owning the full stack from data warehousing and ETL through to executive dashboards and advanced analytics.

  • Impact: Increased OTIF by 25%, identified millions in excess & obsolete inventory, detected ~1% of revenue in out-of-stock sales loss
  • Team Leadership: Built and lead a team of PhD-level data scientists and engineers, supporting senior leadership across the group
  • Full-Stack Data: Delivered centralised global reporting and Streamlit dashboards (with Entra SSO), replacing fragmented legacy systems with a universal architecture
  • KPI Strategy: Designed EOS Level 10 executive scorecard aligning KPIs with operational priorities
  • Advanced Analytics: Customer segmentation, margin optimisation, and strategic growth initiatives
  • AI-Assisted Development: Leveraging Claude Code to accelerate delivery of data products and pipelines
European Data Scientist Apr 2023 - Jan 2025
Nexus Brands Group

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. Promoted to Global Lead Data Scientist based on this work.

Data Scientist May 2022 - Apr 2023
Christies Direct (now part of Nexus Brands Group)

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.

Astrophysics PhD Sep 2017 - Feb 2022
Queen's University Belfast

Joint venture with Randox Laboratories developing statistical techniques for astrophysical and biomedical analysis. Developed algorithms for large-scale statistical analysis of below-noise-floor signals, leading to novel discoveries of stellar nanoflares. Created image feature recognition software achieving 98.8% reduction in processing times (saving 600+ seconds), key component of biochip diagnostics pipeline in $12B industry.

2023
Nanoflare Activity on Fully Convective M-dwarf Stars
Grant et al. The Astrophysical Journal
2020
Statistical Evidence for Stellar Nanoflare Signals in M-type Lightcurves
Dillon et al. The Astrophysical Journal
2019
Monte Carlo Techniques for Nanoflare Detection in Solar Active Regions
Jess et al. The Astrophysical Journal
MSci Physics, First Class Honours Sep 2013 - Jun 2017
Queen's University Belfast

Seagate bursary recipient. Head of peer mentor scheme.