I build AI products for consequence.

The evaluation comes first.

AI Product Manager
AI safety, trust & governance
Insurance, carbon credits, regulated markets
Founding technical team (#5) at CarbonPool
Ex-McKinsey · IPCC AR6, PhD

I built and shipped two production AI agents that cut manual research from several days to under ten minutes, so a counterparty gets screened in one sitting instead of one week. Each was gated on an evaluation pipeline I built first. The 0-to-1 risk model underneath them backed $XX M
in pre-underwritten premiums.

Get in touch See my work

Founding technical team member, CarbonPool

Production AI agents shipped, gated on evaluation

~97%

Faster analytical turnaround, rebuilt with Claude Code

$XX M

Pre-underwritten premiums, behind the 0-to-1 risk model

IPCC AR6

Contributing Author · 23 papers · 4,000+ citations

Career Arc

Four chapters, one converging thread

Four chapters, each one adding a capability, converging on AI product leadership in regulated, high-stakes domains.

Chapter 4

CarbonPool (Insurance / Climate-Risk Tech)

Director of Climate Risk Products & Applied AI

& Technical Team, Founding Member (Employee #5)

Founding technical team member (#5). Built the 0-to-1 risk model behind a first-of-kind carbon-credit insurance product, then shipped two production AI agents, all under insurance liability.

Capability addedBuilding and evaluating AI where a person signs the output.

Chapter 3

Risilience (Climate Risk Analytics, SaaS)

Lead Climate Risk Modeller

Co-developed the Scope 3 methodology behind a Net-Zero Planner SaaS, built the data pipelines, and designed the platform storylines serving enterprise clients.

Capability addedShipping a data product end to end.

Chapter 2

McKinsey & Company (Sustainability Practice, Consulting)

Research Science Specialist (Climate Data Scientist)

Primary specialist on TCFD physical-risk disclosures for enterprise clients, translating asset-level climate analysis into decisions a C-suite would act on.

Capability addedTurning technical analysis into executive product under a regulated frame.

Chapter 1

Applied research (7 years)

Postdoctoral Researcher & PhD student

As an IPCC AR6 Contributing Author I quantified uncertainty for the Paris Agreement, work that is part of 23 peer-reviewed papers and 4,000+ citations in journals including Nature Climate Change and Nature Geoscience. I won the CHF 760K SNF Ambizione grant as sole investigator, then declined it to build commercial product instead.

Capability addedMeasuring what a model does and does not know.

The thread is one decision repeated:
develop the evaluation first, because the signature is mine.

See my work

Guiding Principles

Two convictions that shape how I build

Evaluate before deploying, and keep high-stakes decisions understandable and contestable.

“…social justice is not only a goal to be safeguarded after technologies are deployed, but a condition that must shape their very design from the outset.”
by Pope Leo, Magnifica humanitas, 109

“…when data and algorithms influence credit distribution, personnel selection or access to services and opportunities, it is necessary that decisions be understandable, contestable and subject to oversight, so that individuals are not reduced to mere profiles.”
by Pope Leo, Magnifica humanitas, 164

About

The common thread is liability

I build AI products for consequence: production AI agents and risk models in insurance, carbon credits, and counterparty due diligence. The common thread is liability. A person signs the model's output, so I develop the evaluation before the product.

I am the founding technical team member (#5) at CarbonPool, an insurance startup, where I led the product and data strategy for the risk-modelling stack behind the world's first in-kind carbon-credit insurance product, and built and shipped production AI agents with Claude Code. Seven years of applied research is the reason the rigour holds: uncertainty quantification for the IPCC, then three years shipping AI under insurance deadlines, and the habit survives the commercial pressure.

I can brief a board member, an underwriter, and an engineer in the same afternoon and lose none of them. That is the job.