Machine Learning Scientist II
at Expedia Group
March 2025 - present, 100%
MLS2 in the Supply Partner Machine Learning Science team.
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My projects and responsibilities as machine learning scientist included the following.
Data Science and Research
building large-scale ML solutions for real-world problems revolving around lodging
working in a fast-paced and highly-skilled team
working with billion-scale datasets
Machine Learning Engineering
being a full stack machine learning scientist
optimizing deployment process, ML life cycle components and smoothening scientists-t0-engineers interface and communication
Docker, Airflow, GH Actions, CI/CD, Kubernetes, Splunk
Other
stakeholder alignment (product, TPMs, and leadership)
Data Scientist
at Quanthome
Aug. 2022 - Oct. 2024 (2 yrs 3mos, 100%)
Quanthome is a data science startup based in Lausanne, aiming at digitalizing the Swiss real estate market. It provides services allowing to strategise and simulate performance, in order to enhance investment methodologies. One of the main goals is to bring transparency and regularize the financial and environmental impacts of real estate entities.
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My projects and responsibilities as data scientist included the following.
Data Science and Research
leading machine learning projects (Python, XGBoost, scikit-learn) and supervising data science interns
research collaboration with the Center for Risk Management of Lausanne (ESG analysis and climate risk)
Machine Learning Engineering
implementing complete model life cycles
in charge of MLOps (CI, model versioning, monitoring and deployment) (GitHub Actions, MLFlow, Streamlit)
Data Engineering
designing, building, and maintaining ETL pipelines (Postgres, Airflow)
database management and architecture, data migrations (Postgres, psycopg, alembic)
Reasearch Developer
at EPFL
Aug. 2021 - Feb. 2022 (7mos, 40%)
The Laboratory for Topology and Neuroscience at EPFL is directed by Professor K. Hess-Bellwald and is affiliated to the mathematics department. It aims at using tools coming from algebraic topology to tackle complex real-life data challenges, with applications to life sciences (in particular, computational neurosciences) and machine learning problems.
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As a research developer, I collaborated with Dr. Nicolas Berkouk to make a survey about a powerful topological data analysis tool called 'Levelset Zigzag Persistent Homology'. In realizing this project, I also implemented a Streamlit web application allowing for an intuitive visual guide of how using this tool works. The project included the following features.
mathematics research paper redaction
python web application
topological data analysis
emphasis on diagrams and data visualisation
Data Science Intern
at EPFL
Dec. 2020 - July 2021 (8mos, 40%)
The Laboratory for Topology and Neuroscience at EPFL is directed by Professor K. Hess-Bellwald and is affiliated to the mathematics department. It aims at using tools coming from algebraic topology to tackle complex real-life data challenges, with applications to life sciences (in particular, computational neurosciences) and machine learning problems.
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I worked on a project together with a data science student and under the supervision of two PhD students. We developed a pipeline designed to study the COVID19 spreading process in the canton of Geneva. The project included the following features.
graph theoretical analysis
statistical data analysis
topological data analysis
building the project with Docker
developing a Streamlit web application
This project, as a whole, was supervised by Professor Kathryn Hess Bellwald.