CV

Summary

Applied Data Scientist and Consultant with 7+ years of experience delivering production ML/GenAI solutions across finance, healthcare and the public sector. Drove £8M+ in projected savings across a £10M programme portfolio. PhD in Engineering from University of Cambridge with a track record of leading cross-functional teams from concept to production and driving executive adoption.

Professional Experience

Appointments

Education

Skills

Skills - Time-series forecasting, Classification, Residual Value Evaluation, Image, Signal and Noise processing, Image Segmentation

Language /libraries - Python (Numpy, Scipy, Pandas, Matplotlib, OpenCV, scikit-learn, PyTorch, Tensorflow), MySQL, MATLAB

Platform - Azure (OpenAI, AI Foundry, ML Lab, Function App, PowerPlatform, Teams apps), Appian, KNIME, GitHub, Postman <!– | Analytics & ML | Engineering & Cloud | Delivery & Governance | |——————————————–|—————————————————|———————————————| | LLM apps & RAG; prompt engineering | Python, SQL (T-SQL/Postgres/MySQL), Git/GitHub | Agile/Scrum, Jira/Azure Boards | | NLP: sentiment, emotion, NER, summarisation| Azure ML, Azure OpenAI, AI Foundry | Use-case discovery & ROI modelling | | Computer vision: detection, segmentation | Azure AI Search, Functions, App Service, Storage | Executive training & enablement | | Time-series forecasting, anomaly detection | MLOps: CI/CD, model serving, monitoring | Responsible AI & AI security (guardrails) | | Residual value modelling (EV fleets) | Power Automate/Apps, Microsoft Graph, Teams/SP | Documentation, whitepapers, workshop design |

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