Built AI based photo logging for tracking meals, becoming Zoe’s key feature.

• Implemented low latency two-stage semantic search with Hypothetical Document Embeddings (HyDE) and RAG using a vector database on Vespa.
• Finetuned models on internal dataset and built an evaluation framework to measure AI task performance to a rigorous standard with ML metrics.
• Integrated LLM providers in a single gateway - OpenAI, Gemini and self-hosted.
• Developed and managed a range of Kotlin / Spring Boot microservices on kubernetes.
• Architecture design and iteration of our stack to support 10x scale-up and low latency AI.

Developed and deployed realtime product ranking and recommender models to the Bloom & Wild website and app, delivering substantial uplifts in revenue.

• Built out serverless ML and data infrastructure on AWS using terraform.
• Identified AWS savings totalling 25% of the business’ AWS spend.
• Improved API performance, e.g. reducing AWS Lambda API p95 latency by 10x.
• Introduced and deployed MLOps tooling such as mlflow and Feast.
• Raised engineering standards, e.g. use of mypy, CI pipelines and a python community of practice.
• Line management, introducing agile working practices and mentoring in ML techniques.

Led a cross-disciplinary squad of engineers and data scientists.

• Developed and deployed ML models to predict retention probability, detect anomalous trading.
• Trained XGBoost models to forecast flight price changes and highlight deals to customers.
• Delivered new feature flagging and experimentation tooling used across the entire tech stack.
• Introduced sagemaker, dask, databricks and mlflow to the data science discipline.
• Hired, developed and promoted data scientists up to principal level.

As the first data scientist hire of Vodafone UK, I helped scale up the function, training and deploying the first models to production and delivering significant uplifts in personalised CRM campaigns.

• Developed and deployed collaborative filtering recommender system for personalised marketing.
• Trained models to determine ‘Next Best Action’ to support agents with customer calls.
• Led knowledge sharing, running python workshops and tutorials.
• Led interviewing and training of Data Science hires in Vodafone UK.

Trained and deployed models for music machine learning and recommendation, e.g. building a voice classifier and collaborative filtering music recommender system for major music label using their large corpus of audio data.

Collaborated with product team to develop novel algorithms for personalising music recommender systems. Designed and prototyped recommender system concepts that were incorporated into the Beosound Moment product.