👋 About Me

I’m Andrew Peters (PhD), a Data Scientist specialising in Data Visualisation, RShiny development and applied machine learning.

My work bridges sports analytics, finance, and pharmaceutical R&D — turning complex datasets into clear, actionable insights.

🎯 My Professional Focus

I specialise in:

  • Data Visualisation and design — communicating complex results to non-technical audiences through clear visual design
  • Interactive data visualization — developing dashboards and analytical tools using RShiny, Tableau, and ggplot2
  • Machine learning for performance analysis — applying models such as XGBoost and Mixed Effects to real-world problems

Across every role, I focus on helping organisations make data-driven decisions that are intuitive, transparent, and impactful.

💼 Professional Experience

Data Scientist – Pfizer (Jan 2025 – Present)

  • Develop and maintain RShiny apps used across global manufacturing and quality teams.
  • Member of a small UI/UX design group responsible for the front-end design of deployed analytical apps.
  • Support global adoption of the Statistical Process Investigator (SPI) app, ensuring clear communication of site-level quality data.

Senior Data Visualisation Specialist – Central Bank of Ireland (Oct 2023 – Nov 2024)

  • Created internal RShiny dashboards for cross-departmental reporting.
  • Designed visuals for external economic publications to improve data accessibility and impact.
  • Delivered training on data visualisation principles to upskill analysts across teams.

Data Scientist – Leicester City Football Club (Feb 2021 – Sep 2023)

  • Built analytical models to evaluate team and player performance using event and tracking data.
  • Developed a suite of custom RShiny apps to automate visualization generation for coaches.
  • Designed and deployed dashboards across Performance Analysis, Sports Science, and Recruitment.
  • Presented at the 13th World Congress in the Performance Analysis of Sport (2022) — “A Machine Learning Approach to Identify Pressing Targets in Football.”

🎓 Education

  • PhD Data Science — Middlesex University (2021–2024)
    • Research focused on tactical concepts of pressing and rest defence in football using machine learning.
  • MSc (High 1.1), Genomics Data Science — University of Galway (2018)
    • Specialised in bioinformatics, machine learning, and data-driven genomics.
  • BSc (High 2.1), Genetics — University College Dublin (2017)

🧑‍🏫 Teaching & Outreach

I have designed and delivered data visualization workshops (1–3 hours), covering:

  • Technical training in R and ggplot2 — building reproducible, well-designed visuals
  • Conceptual sessions on data storytelling, design thinking, and effective communication

Workshops have been run for staff at the Central Bank of Ireland, helping raise internal visualisation standards and analytical literacy.

🧰 Technical Skills

Languages: R, Python, SQL
Visualisation Tools: RShiny, ggplot2, Plotly, Tableau, Power BI
Machine Learning: Scikit-Learn, XGBoost, Mixed Effects Modeling
Cloud & Infrastructure: AWS, API integration
Design: UI/UX for analytical apps, dashboard automation

📚 Selected Publications

  • Counterpressing and Rest Defence in Football (Journal of Sports Analytics, 2025)
  • Creation of a KPI to Evaluate Possession Retention (Journal of Sports Sciences, 2024)

View publications → Football Analytics Project

🏁 Summary

I’m driven by the challenge of making data both insightful and intuitive — building tools and visuals that help others understand complex systems, whether in sport, finance, or science.

My mission is simple: combine analytical rigor with design thinking to turn data into understanding.

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