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Current Position
Current Position
Senior Data Scientist
Senior Data Scientist
John Lewis Partnership, London
Since March 2025
• Delivered £2M business benefit through replenishment safety stock optimisation, increasing product availability while reducing overstocking. Led discovery trial through to large-scale adoption. Built supply chain simulation & demand forecasting models, integrated into replenishment workflows. Partnered with supply chain, operations, and commercial teams
• £500k annual business value via distribution centre outbound stock forecasting using hierarchical intermittent time series models, across 2k product categories and 3 distribution centres
• Designed and deployed first-in-business Click & Collect location optimisation, combining data science and OR techniques. Delivered scalable, low-latency solution with Streamlit frontend
• Enabled stakeholder adoption of data-driven decision-making, translating analytical insights into operational strategies through structured storytelling
• Led DS product scoping, solution design, and roadmap ownership, partnering with stakeholders to ensure measurable business value delivery
• Established best practices across DS team, standardising solution architecture patterns and leading technical knowledge-sharing sessions
• Data science mentorship and capability development
Employment History
Employment History
Data Scientist
Data Scientist
OctaiPipe (t-dab.ai), London E1
April 2022 - March 2025
• Main contributor to 7 commercial & industrial ML projects (incl. 2 Innovate UK), delivering edge ML solutions for fault detection, HSE compliance, and risk modelling
• Lead DS contributor to reinforcement learning in company pivot to data centre energy optimisation
• Designed and deployed RAG/LLM infrastructure (LlamaIndex, FastAPI, Kubernetes, Weaviate)
• Integral part of product team delivering first version of company’s main edge-IoT ML platform, QA testing. Productised state-of-the-art ML algorithms and trustworthy AI features
• Delivered data insights to customers; authored white papers and company blog posts. Led customer onboarding, created product demo videos. Project scoping
Postdoctoral Scholar in Physics
Postdoctoral Scholar in Physics
Department of Physics and Astronomy
The University of Kentucky
August 2021-February 2022
Education
Education
PhD in Physics
PhD in Physics
New York University
Thesis Adviser: Professor Massimo Porrati
2021
BSc in Physics
BSc in Physics
The Hong Kong University of Science and Technology
First-Class Honours
2014
Skills & Languages
Skills & Languages
Core:
Python, SQL, Git, Linux
Machine Learning & Forecasting:
Supervised & unsupervised learning, time series forecasting, anomaly detection, optimisation, explainability, model auditability
Hierarchical Bayesian models (NumPyro), intermittent demand forecasting, multi-time-series modelling, recursive ML forecasting (XGBoost / skforecast)
Pandas, NumPy, SciPy, Scikit-Learn, TensorFlow, PyTorch, Transformers, XGBoost, SHAP
Optimisation & Simulation:
Supply chain optimisation, simulation modelling, reinforcement learning
OR-Tools, Gymnasium, stable-baselines3
LLMs & Generative AI:
Retrieval-Augmented Generation (RAG), prompt engineering
LlamaIndex, Weaviate (Vector Database), Google Agent Development Kit
MLOps & Production ML:
CI/CD, ML pipelines, model monitoring, architecture design
Vertex AI Pipelines, GCP, Docker, Kubernetes, Azure, Dataiku
Data Platforms:
Snowflake, dbt, InfluxDB
Visualisation & Analytics:
Storytelling & insight communication
Streamlit, Tableau, Grafana, Matplotlib, Plotly, PyDeck
Leadership:
Stakeholder engagement, mentoring, product roadmap ownership
Value-driven problem framing, data-driven decision enablement, Agile
Domain:
Retail & large-scale supply chain optimisation, industrial ML use cases, violin making
Publications
Publications
A full list of my publications in physics is available at
Google Sites
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