Open-source BI for the modern-data-stack.Building ❤️ and trust between data teams and data users.

ML Engineer and technical Product Manager. Freelance projects include: - NLP with human-in-the-loop AI platform for a global asset manager - Personal loans product for a leading bank in an emerging market. Including ML-powered credit scoring for thin file customers. - Motor insurance risk scoring product for a start-up insurtech in an emerging market.Tech: Python, go, C, js react. AWS, GCP. Kubernetes, docker, terraform, ci/cd, serverless.Machine learning models: GLMs, GAMs, survival analysis, bayesian methods, tree-based methods, pretrained nets, deep learning, topic extraction, dimensionality reduction, explainable AI.

Tech Lead for Risk Analytics product.

Developing statistical models to price risk for insurance.

Client facing data scientist and knowledge engineer. Worked with tier 1 banks and asset managers to provide real-time risk data.Developed a natural language processing algorithm to extract quantities from news articles.

Soton Quants is a regular meetup of mathematicians, engineers, developers, and economists with an interest in quantitative finance.Delivering regular workshops to give an introduction to quant finance. Hosted algorithmic trading competition using existing backtesting platforms.

Offering a range of support services to undergraduate and postgraduate students with disabilities or other barriers to education. Responsibilities include laboratory support, `buddy' support, note-taking and library services assistance for engineering and science students.

Currently applying techniques developed during my dissertation to further prognostics for munitions systems. Initial research involves developing synthetic data from crack length propagation models in rubber-like materials. The aim of the project is to provide a convincing case for munitions systems prognostics using an embedded architecture.

Awarded an undergraduate research scholarship as part of the SURE 2012 scheme: investigating machine learning algorithms and modern signal processing methods to develop a system for the self-diagnosis of heart murmurs and extrasystoles with the overall aim of reducing the time to diagnose cardiovascular diseases.

Granted a departmental bursary to assist the research team in the ‘Rolls Royce University Technology Centre’. The majority of research was carried out in collaboration with Network Rail to develop ‘Wireless Sensors and Energy Harvesting for Intelligent Railway Infrastructure’. The project involved the design of a solar simulation environment for characterising PV solar cells in order to support this research.