Dr. Christopher Dillon

As the Global Lead Data Scientist at Nexus Brands Group, I now operate across all 18 businesses within the group. Building on my previous European remit, I play a core role in the formation of our new Global Finance and Data Analytics Department, a strategic initiative to centralize finance and data operations globally. Our mission is to elevate data-driven decision-making and drive operational efficiencies at scale.

Key Responsibilities:

• Team Leadership: Building, hiring, and managing a high-performing global data team to support senior leadership across the group.
• Standardization: Designing and implementing a universal data and reporting architecture to replace fragmented legacy systems, ensuring consistency, transparency, and speed in business intelligence.
• Self-Service Analytics: Developing secure, tailored dashboards using Streamlit, with Entra SSO implemented across dashboards and BI.
• Operational Reporting: Delivering robust reporting suites to support core supply chain functions, including:
  • OTIF (On Time In Full) performance: Identified gaps, implemented tracking, and led initiatives that increased OTIF by 25%.
  • Excess & Obsolete (E&O) Stock management: Built tracking and visibility frameworks that identified millions in excess and obsolete inventory.
  • Out-of-Stock (OOS) monitoring: Developed root-cause diagnostics that enabled detection and reduction of OOS-related sales loss worth approximately 1% of revenue.
• KPI Strategy: Designed and implemented an EOS Level 10 (L10) executive scorecard, aligning core KPIs with operational priorities to support data-driven decision-making and execution discipline.
• Advanced Analytics: Scoping and delivering data science initiatives focused on customer behavior, margin improvement, and strategic growth.
• Operational Delivery: Managing the global data team's workload across reporting and analytics pipelines, ensuring value delivery aligned to business priorities.

This role extends my work in unifying data systems and delivering customer-centric analytics — enabling smarter, faster, and more confident decision-making across the Nexus Brands portfolio.

Transformed the data function for 5 European businesses across tattoo, beauty, and pet grooming supply. Consolidated fragmented data sources into a universal data warehouse, enabling consistent automated reporting. This role laid the groundwork for the global structure I now lead, and resulted in my promotion to Global Lead.

Built 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 based on this work.

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

My PhD project title was "Observations and Modelling of Intensity Time series for Biomedical and Astrophysical Applications". A redacted copy of my thesis is available at that link. This PhD was a joint venture between Queen's University Belfast, and Randox Laboratories to develop cutting-edge statistical techniques with application in astrophysical and biomedical analysis.

During the PhD I developed very strong data analysis skills, primarily through the development of algorithms for the large-scale statistical analysis and modelling of extremely challenging below-noise-floor signals, which were applied to astrophysical and to industrial biomedical datasets. My development and application of statistical techniques led me to novel discoveries of stellar nanoflares, which hold the potential to answer key questions about the nature of flaring in stars.

Applying those same techniques to biomedical data allowed for the development of cutting-edge noise suppression and dynamic range software. As part of this pipeline, I created bespoke image feature recognition software. This recognition software identifies key features within an image in around a second, and has led to a 98.8% reduction in downstream processing times (a saving of over 600 seconds), forming a key component of the data analysis pipeline providing competitive advantage to Randox in the field of biochip diagnostics (an industry valued at $12 billion). These results highlight the direct applications of my astrophysical data analysis skills to industrial needs.

Written and spoken communication skills were extensively developed, through academic publications, annotated code pipelines, and industrial technical documents, as well as presenting at numerous conferences, workshops and catchup meetings with industry partners. The synthesis of industry and academic experience has allowed me to develop excellent communication skills, and the opportunity to collaborate with biomedical colleagues from a range of different skill-sets and job-roles. I developed extensive coding experience, primarily working in IDL, as well as Python. I also worked as a Level 1 and 2 Lab demonstrator. I greatly enjoyed the opportunity to teach and work with large groups of students (40+), and I consistently achieved excellent feedback in student evaluation forms.

Role required leading an investigation into a manufacturing defect. Required strong interpersonal skills, in order to interact with team members and deliver the changes required. Emphasis on presenting findings to management, requiring confidence and strong presentation skills. Developed my personal responsibility, as I undertook self directed tasks to solve this manufacturing problem. Gained experience with R, as well as Six-sigma manufacturing philosophy.