Five years building index strategies at MSCI & Morningstar — now building AI systems for investment teams. I build end-to-end: the algorithm and the product around it. Most useful at the seam between finance, AI, and product.
Audits, pilot builds, and ongoing capacity for teams putting AI to work on investment problems — research, data, agents, the product layer.
A hard look at your AI or trading system — what to build, what to kill, where the risk actually hides. You get a memo you can act on, not a deck.
A working end-to-end proof — a Claude integration, an agent system, a backtest engine — and the interface that exposes it. Fixed scope, fixed price.
Fractional AI-for-investment-team capacity — architecture reviews, agent builds, and the seam work between your quants and your product.
Scoped on a call. Booking from August 2026.
Built Index AI Analyst — an internal assistant wired into MSCI's index data so analysts and EMEA institutional clients can interrogate methodology in plain language. Delivered custom ESG, climate-transition, and thematic index strategies end-to-end, from client spec to delivery.
Value and growth strategies beat the proprietary benchmark by 1.5% and 3% over 15-year backtests. An SDG-based ESG strategy lifted Sharpe 0.15 over five years. Automated the client data pipeline and gave back 10+ hours a week. One of 100+ recipients of the Morningstar Geek Award.
Live experiments at the finance–AI seam — portfolio agents, trading copilots, and factor research, built in public.
Morningstar then MSCI on the research side — index methodology, ESG, climate, the quant work behind benchmarks institutions actually hold. Before that, product and growth at early-stage startups, where I learned to ship.
Now I work at the seam: designing the model and building the product that makes it usable. I ship small and measure fast.