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I'm Guillaume Pealat, a data scientist and financial engineer with over 15 years of experience in derivatives. I love turning complex data into clear, client-focused solutions and leading teams to build innovative investment and technology platforms. I’m passionate about technology and have recently designed Gallium’s data science platform while contributing to open-source projects like QuantLib. Currently, I lead the technology stack at Gallium Investment Partners, building a high-availability data science platform, implementing MLOps with DVC and MLFlow, and developing quantitative strategies such as synthetic data generation, market regime clustering, and risk analytics using advanced statistical methods.…I'm Guillaume Pealat, a data scientist and financial engineer with over 15 years of experience in derivatives. I love turning complex data into clear, client-focused solutions and leading teams to build innovative investment and technology platforms. I’m passionate about technology and have recently designed Gallium’s data science platform while contributing to open-source projects like QuantLib. Currently, I lead the technology stack at Gallium Investment Partners, building a high-availability data science platform, implementing MLOps with DVC and MLFlow, and developing quantitative strategies such as synthetic data generation, market regime clustering, and risk analytics using advanced statistical methods.

Guillaume Pealat

Data Scientist, Project Manager, Data Analyst

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I'm Guillaume Pealat, a data scientist and financial engineer with over 15 years of experience in derivatives. I love turning complex data into clear, client-focused solutions and leading teams to build innovative investment and technology platforms. I’m passionate about technology and have recently designed Gallium’s data science platform while contributing to open-source projects like QuantLib. Currently, I lead the technology stack at Gallium Investment Partners, building a high-availability data science platform, implementing MLOps with DVC and MLFlow, and developing quantitative strategies such as synthetic data generation, market regime clustering, and risk analytics using advanced statistical methods.…I'm Guillaume Pealat, a data scientist and financial engineer with over 15 years of experience in derivatives. I love turning complex data into clear, client-focused solutions and leading teams to build innovative investment and technology platforms. I’m passionate about technology and have recently designed Gallium’s data science platform while contributing to open-source projects like QuantLib. Currently, I lead the technology stack at Gallium Investment Partners, building a high-availability data science platform, implementing MLOps with DVC and MLFlow, and developing quantitative strategies such as synthetic data generation, market regime clustering, and risk analytics using advanced statistical methods.

Available to hire

I’m Guillaume Pealat, a data scientist and financial engineer with over 15 years of experience in derivatives. I love turning complex data into clear, client-focused solutions and leading teams to build innovative investment and technology platforms. I’m passionate about technology and have recently designed Gallium’s data science platform while contributing to open-source projects like QuantLib.

Currently, I lead the technology stack at Gallium Investment Partners, building a high-availability data science platform, implementing MLOps with DVC and MLFlow, and developing quantitative strategies such as synthetic data generation, market regime clustering, and risk analytics using advanced statistical methods.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

French

Fluent

English

Fluent

Korean

Beginner

Work Experience

Data Scientist & Financial Engineer at Gallium Investment Partners

October 1, 2023 - Present

Founding Partner and lead of the technology stack. Built a High Availability hybrid cluster using Proxmox and Docker to reduce costs versus full cloud hosting (Proxmox, Ceph, S3). Lead analysis of quantitative strategies, synthetic data generation using GANs for risk management, and market regime clustering with k-means and Wasserstein distance. Implemented MLOps framework using DVC and MLFlow.

Head of Financial Engineering / Quantitative Research at Tradition / CARAX

July 1, 2007 - October 1, 2023

Managed a team of 4 engineers. Developed the quantitative library (contributor to open-source QuantLib). Initiated projects to track client preferences pre-GDPR and proposed products via recommendation algorithms. Created and implemented a methodology to calibrate vol target products based on k-means and Wasserstein distance.

Pre Sales Consultant & Project Manager at Summit / Mysis

January 1, 2001 - July 1, 2007

Supported and managed accounts in Europe; dispatched to Asia (2004-2007) to grow the customer base; acted as Project Manager at HanaBank.

Technical Consultant at Ubitrade

January 1, 2000 - January 1, 2007

Provided technical support to traders (CDC IXIS).