Data Science Consultant at Xantura (Newton Europe) · ex-British Airways and BBC · Toronto
I build models that change real decisions, and the pipelines that keep them working in production. My background is financial economics, and I've worked on risk, pricing and experimentation in aviation, media, fintech and the public sector. I like owning the whole job, from the raw data to the conversation with the people who use the results.
- Xantura (Newton Europe): I build risk-scoring models that rank 40k+ accounts across 1.5M+ sensitive public-sector records, so frontline teams know where to act first.
- British Airways: I built pricing and market-share forecasts from 200M+ ticket records (~5% MAPE) and presented them to American Airlines and Japan Airlines.
- BBC: I ran A/B tests on BBC Sounds (5M+ monthly users). The winning variant lifted click-through by 6%.
- Nova Money (fintech startup): I worked directly with the CEO on onboarding experiments that helped triple monthly sign-ups, from ~1.5k to ~4.5k.
Stack: Python · SQL · scikit-learn · Airflow · dbt · Azure Data Factory · Snowflake · Databricks · AWS · Power BI
Certified: Databricks Data Engineer Associate · AWS Machine Learning Engineer Associate
- last-job-search: an AI agent system that runs a whole job search from one page. It scores thousands of postings, writes fact-checked tailored applications and drafts the networking messages.
- openroles: a Python library and MCP server. Give it a company name and it pulls every open role straight from that company's hiring system (Greenhouse, Lever, Ashby, Workday and more). On PyPI.
- CaseSignal: a credit-risk prototype inspired by my work at Xantura. It ranks accounts by risk, and adding auditable AI signals from case notes raises precision in the top 10% by 14%.
- CopulAX (contributor): a JAX library for copula modelling and probability distributions. I'm adding support for univariate distributions, with tests for the edge cases.
I love to cook. When I'm not in the kitchen, I'm usually travelling or watching films, and I log every film on Letterboxd.

