Description

Senior Data Scientist with 15 years of experience delivering machine learning and AI solutions for complex, real-world problems across healthcare, climate, energy, and industrial domains. Proven track record of leading cross-functional projects, collaborating with stakeholders, and translating large-scale data into actionable insights and decision-support tools. Experience spanning academia and industry, with expertise in time series analysis, data-driven modelling, and AI-driven innvoation.

Domaines d’expertise

Langues

Anglais
Capacité professionnelle complète
Français
Capacité professionnelle complète
Allemand
Notions
Roumain
Bilingue ou natif

Préférences en matière de lieu de travail

Accepte de travailler sur site

Lausanne (jusqu’à 50 km)

Swiss Statistical Design and Innovation
Senior Data Scientist
AGENCE & SSII
septembre 2025 - février 2026 (5 mois)
Fribourg, Switzerland
• AI/ML for energy forecasting: Developed a validation and backtesting framework for energy demand forecasting, benchmarking and optimizing tree-based, neural network, and transformer-based models, leading to consistent performance improvements across providers for intraday forecasting (Python, PyTorch).
• AI/ML applied data science: Led the technical delivery of end-to-end AI/ML solutions for manufacturing anomaly detection and sales forecasting, including presentation of results to stakeholders. Led the design and execution of an audio signal classification project. Completed proof-of-concepts were validated and funded for the next project phase.
Machine learning Deep Learning Python Forecasting Anomaly detection
Volv Global SA
Senior Research Data Scientist
INDUSTRIE PHARMACEUTIQUE
juillet 2023 - août 2024 (1 an et 1 mois)
Lausanne, Switzerland
• Machine learning for healthcare: Developed ML methods for patient classification and early disease diagnosis across multiple disease areas using real-world data, improving predictive performance by 10-20% over clinical domain experts
• Patient group discovery and explainable AI: Applied clustering, explainability, and rule extraction to identify patient subgroups and characterize subgroup-specific predictive factors, delivering interpretable findings to pharmaceutical partners
Machine learning Pharma Explainable AI Python Deep Learning
Swiss Data Science Center, EPFL
Senior Data Scientist
CENTRES DE RECHERCHE
septembre 2017 - décembre 2022 (5 ans et 3 mois)
Lausanne, Switzerland
• Scientific ML: Worked on interdisciplinary projects in collaboration with ETH-domain laboratories, including representation learning for climate science, physics-informed ML for atmospheric prediction, and forecasting of extreme events.
• Machine learning and causal inference: Developed robust high-dimensional regression methods for climate change detection under interventions and transfer learning setings with good extrapolation properties (Python).
Machine learning Data science Project Management Climate science Causal reasoning