Sébastien Forestier

Data Scientist

https://www.opentalent.in/sebastien-forestier

Member since June 26, 2026

Key Strengths

Extensive experience with Python, particularly in AI/ML and Reinforcement Learning contexts.
Demonstrated ability to work on complex, research-oriented projects involving LLMs and multi-agent simulations.
Proficiency in using Jupyter Notebooks for data science and research workflows.
Experience with various development tools and scripting (Shell, CMake).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are predominantly personal and research-focused, indicating a strong drive for independent exploration and contribution to open-source. The diversity of technologies (Python, Rust, TypeScript, Java) and domains (LLMs, RL, decentralized apps) suggests adaptability. However, the lack of team-based or industry-specific projects makes it difficult to fully assess cultural fit for a collaborative, production-oriented Data Scientist role.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest a strong focus on technical research and development.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

gossip

September 10, 2025 – Present

Decentralized messaging app on Massa

View Project

LLM-Culture

February 20, 2024 – Present

Code for the "Cultural evolution in populations of Large Language Models" paper

View Project

docs

April 18, 2023 – Present

Massa Protocol Documentation

View Project

vivarium

March 25, 2023 – Present

Multi-agent simulator in Jax for research and teaching in AI & ALife

View Project

lamorel

February 1, 2023 – December 11, 2025

Lamorel is a Python library designed for RL practitioners eager to use Large Language Models (LLMs).

View Project

IMGEP

March 26, 2019 – January 22, 2020

Open-source code for Intrinsically Motivated Goal Exploration Processes

View Project

APEX

June 23, 2017 – November 8, 2018

Autonomous exploration, active learning and human guidance with open-source Poppy humanoid robot platform and Explauto library

View Project

NIPS2016

October 3, 2016 – May 22, 2018

Autonomous exploration, active learning and human guidance with open-source Poppy humanoid robot platform and Explauto library

View Project

poppy-docs

September 3, 2015 – December 19, 2022

Documentation of the whole poppy platform

View Project

explauto

March 7, 2014 – July 16, 2020

An autonomous exploration library

View Project

Key Strengths

Extensive experience with Python, particularly in AI/ML and Reinforcement Learning contexts.
Demonstrated ability to work on complex, research-oriented projects involving LLMs and multi-agent simulations.
Proficiency in using Jupyter Notebooks for data science and research workflows.
Experience with various development tools and scripting (Shell, CMake).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest a strong focus on technical research and development.

Sébastien Forestier

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit