Machine learning (ML) engineer and applied scientist with 7+ years of
experience in probabilistic modeling and full-stack ML systems.
Published author in statistical energy modeling; built ML systems
from R&D to production.
Professional experience
Mar 2024 - Now
Applied AI Scientist at Datadog (Paris,
France)
Building machine learning and algorithmically driven features for
Datadog app.
Designed and implemented a clustering pipeline for log clustering in
production using embeddings.
Designed an algorithm to cluster logs based on tags entropy.
Implemented a fast learning model to detect cyberattacks in
PyTorch.
Interviewed candidates with Data Science Fundamentals
interview.
Sep 2023 - Dec 2023
Founder in residence at Entrepreneur First
(Paris, France)
Part of a curated community of future founders, working to build
globally impactful companies together.
Formed 3 different teams tackling hard problems with software.
May 2019 - Feb 2023
Data scientist in R&D at Deepki (Paris,
France)
Data science improving energy efficiency of buildings.
Working from research to deployment in production of machine learning
models:
A tool to query hundreds of heterogenous databases with HTTP REST
APIs
Developed Bayesian models to estimate building energy consumption,
accounting for spatial-temporal variability (e.g.,floor area, usage
type, climate zone)
Integrated weather and climate variables into predictive pipelines
to inform sustainable energy use
Applied probabilistic programming (NumPyro) for robust inference and
uncertainty quantification
Designed and validated time-series gap-filling models for missing
monthly data, doubling imputation accuracy
Mentoring and training of interns and junior staff members
Feb 2018 - Aug 2018
R&D engineer intern at Stratagem
Technologies (London, UK)
Predictive modelling of NBA basketball in order to advise investment
decisions:
Prediction of the number of Markov transitions remaining during a
game
Implementation of a risk controller framework with property-based
and fuzz testing
Jul 2017 - Dec 2017
Data analyst intern at Amazon (Paris, France)
In charge of business intelligence for international (EU + Japan +
Canada) Ad services:
Responsible for weekly business review, monitoring activity through
KPIs
Ad-hoc analysis on performance, revenue attribution, customer
retention
Sep 2016 - Dec 2017
Mathematics Teaching Assistant at Lycée
Charlemagne (Paris, France)
Conducting oral exams for MPSI students preparing the highly competitive
entrance exams to the French engineering “Grandes Ecoles” (two hours per
week)
Academic experience
2015 - 2019
MSc Engineering at Ecole Centrale Paris (now
CentraleSupélec)
Major: Applied Mathematics in Data Science.
Relevant courses includes: random modelling, convex and discrete
optimization, machine learning, deep learning, reinforcement learning,
natural language processing.
Thesis: Detecting anomalies and monitoring urban furniture energy
consumption
2013 - 2015
Higher School Preparatory Classes at Lycée
Charlemagne (Paris, France)
MPSI - MP*: Two-year undergraduate intensive course in mathematics,
physics, computer science. Ranked 201/3370 of Concours Centrale-Supélec
national entrance exams.
Built a Bayesian model for building-level energy estimation using
physical and climate-based variables; highlighted reproducibility and
uncertainty modeling across Europe.
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