Madrid · Finance · Quantitative Development
I build it to understand it. I understand it so I trust it.
A trading platform of my own: data pipeline, factor engine, execution, and the checks around them. Before that, asset management and a derivatives desk across Boston, Singapore and Manila. I'm in Madrid now, sharpening the data science side at IE.
In every job I've had, I ended up building something.
I interned on ING's derivatives desk in Singapore, working with the traders on pricing and putting together the pitchbooks and credit packs that carry a deal through the bank. Before that I was a Product Analyst at Natixis Investment Managers in Boston, worked in Trade Management at Brown Brothers Harriman, and did Trade Compliance at Arrowstreet Capital. I started out as an investment banking summer intern at Chinabank Capital in Manila.
At Natixis that meant automating a daily report that used to eat half a morning. At Brown Brothers it was a client database. Now it is a trading platform I run myself: a data pipeline that keeps everything point-in-time, a factor engine, an orchestration layer that turns scores into orders, and a dashboard over the top. I'm sharpening the data science side with a masters at IE Business School in Madrid.
Two sides of the same job
Finance meets the code.
Finance
Six months on a derivatives desk covering rates, FX, equities and commodities. Working with traders on swap pricing, and producing the pitchbooks, credit packs and transaction research that sit behind a deal.
- Pitchbooks for structured equity transactions
- Swap pricing alongside the traders
- Credit rationale packs and due diligence
- IPO and book build transaction research
Quant & data
A platform that takes vendor data all the way to live orders. Point in time ingestion, a factor engine, portfolio orchestration and execution, running on my own Kubernetes clusters.
- Point in time data platform on Dagster and k3s
- Factor engine with explicit activation gates
- Portfolio orchestration through to broker execution
- Momentum, mean reversion and pairs strategies
Experience
Selected work
Strategies, pipelines
and the research behind them.
Lean Data Platform
The layer everything else stands on: vendor ingestion, point-in-time fundamentals and corporate actions, orchestrated by Dagster across a GitOps-managed Kubernetes cluster.
Meridian factor engine
A factor engine built around four components: prediction, ranking, regime and risk. Each one has to earn its way into the product.
Argus portfolio orchestration
A portfolio operating system. Strategy sleeves produce targets, a portfolio engine builds the book, risk overlays cap it, and the execution layer works the orders through to the broker.
Fundamental analysis
Eversource Energy equity research
A full valuation case study on Boston's main energy provider, company and industry overview, financial analysis, and a three-statement model with DCF and comps.