Hi, I'm Amaury 👋
Student at Paris Dauphine PSL and 42 School Paris, quant founder at Ellen Capital (+$15M AuM). Passionate about financial markets, technology, and innovation.
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About

I'm currently pursuing a Master's in Finance and Data at Paris Dauphine and attending Ecole 42 to strengthen my technical skills. Passionate about financial markets, mathematics, and innovation, I aim to become an algo trader specializing in commodities, with the long-term goal of launching a commodities-focused fund. Alongside my studies, I work as Quant strategist in a fund I founded, Ellen Capital and run a data-analysis agency and a SaaS startup focused on account abstraction on the blockchain.

Work Experience

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Ellen Capital

Feb. 2025 - not yet
Founder & Chief Investment Strategist – Crypto & DeFi
Founder of a crypto investment fund with $15M in assets under management (AUM), leading the development of our investment thesis focused on a hybrid strategy combining large-cap crypto exposure (BTC, ETH, etc.) with yield generation through decentralized finance (DeFi) protocols. I design and implement custom investment strategies, including the creation and automation of yield-generating vaults. My responsibilities span strategy architecture, protocol curation, automation workflows (smart contracts, bots, infrastructure), and continuous optimization for risk-adjusted performance. I also oversee the technical development required to scale and manage these strategies effectively.
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AXA France

Sep 2024 - not yet
Apprenticeship as a Financial Assistant & Data Manager
At AXA France, within the Plan/Competitiveness team of the Financial Department, I contributed to the 2024-2026 Strategic Plan. My responsibilities included optimizing general expenses through the budgeting process and strategic planning. I worked with tools like Anaplan to generate and support financial reports, ensuring the accuracy of data for strategic initiatives. Additionally, I enhanced financial and operational performance management, analyzed cost structures across various departments, and ensured reliable data collection from different sources. I also contributed to updating and improving strategic models and provided insights into salary costs and expenditure rates.
My Projects

Check out my biggest work

I've worked on a variety of projects. Here are my most successful projects.

Ellen Capital

We manage a $5M crypto fund using a hybrid strategy: large-cap exposure (BTC, ETH) combined with DeFi yield generation. Our edge lies in building and automating custom vaults that deploy capital across curated protocols. We focus on scalable, risk-adjusted strategies powered by smart contract infrastructure.

Python
TypeScript
Solodity
GraphQL

Onchain Science

Onchain Science is a data-driven Web3 consulting agency that helps businesses leverage on-chain analytics to drive growth and gain a competitive advantage. We specialize in customized data pipelines, market intelligence, and strategic insights for product optimization and community engagement.

Python
TypeScript
TrinoSQL
NodeJS

Plentifi

PlentiFi simplifies blockchain integration, making it as user-friendly as Web2. It offers a non-custodial, biometric authentication-based Account Abstraction solution, eliminating the need for seed phrases. With features like multi-device compatibility and seamless developer toolkits, PlentiFi enhances both user and developer experiences.

React
TypeScript
MongoDB
LMDB
Research Papers

I like exploring new ideas

During university, I contributed to research papers, collaborating with peers and professors from diverse fields. It was inspiring to see how curiosity could grow into a full study, uncovering insights that push the boundaries of knowledge. The experience highlighted the power of persistence, innovation, and teamwork in advancing understanding.

  • A

    Applications of Tropical Algebra and Graph Theory in Arbitrage

    Paris France

    Explores the use of Tropical Algebra and Graph Theory to detect arbitrage opportunities by modeling market inefficiencies and optimizing transaction paths.
  • P

    Predicting Horse Race Winners Using a Ranking-Based Machine Learning Approach

    Paris France

    This study explores a ranking-based machine learning model to predict horse race winners, leveraging data scraping, feature engineering, and LightGBM ranking techniques.
Contact

Get in Touch

Want to chat? Just shoot me a email with a direct question and I'll respond whenever I can. I will ignore all soliciting.