20260402 Data Scientist Position Advanced.pdf
Role details
Job location
Tech stack
Job description
Within the Advanced Methods Department, you will contribute to forward-looking methodological developments, with a strong focus on synthetic patients generation, including Bayesian networks, ML-based generative models, and simulation engines, federated analytics approaches ensuring privacy-preserving statistical modelling across distributed datasets, and upcoming data science innovations. As a Data Scientist, you will work at the crossroads of machine learning, causal inference, and advanced statistical modelling. You will be involved in designing, developing, and implementing innovative computational pipelines.
Requirements
We are looking for a motivated and rigorous Data Scientist with the following background:
- MSc (or PhD) in Data Science, Statistics, Computer Science, Applied Mathematics, Biomedical Engineering, or related field.
- 3 to 5 years of experience, ideally in the healthcare sector (pharma, CRO, medtech, biotech, or academic research).
- Proven ability to code in Python (mandatory)
- Familiarity with Bayesian modelling, generative models, or causal inference is a strong asset.
- Strong problem solving skills and appetite for methodological innovation.
- Ability to work in a multidisciplinary environment and communicate technical subjects clearly.
- Fluency in English.
- Autonomy, organization skills, curiosity, and team spirit.
Missions
- Develop and implement algorithms for synthetic patient generation using ML and Bayesian networks.
- Contribute to the development of federated analytics pipelines.
- Participate in innovative methodological research and prototyping.
- Contribute to the preparation of scientific and technical documentation (methods, interpretation, reports).
- Support biostatistical teams with advanced modelling components when needed.
- Participate in internal training and knowledge sharing activities.
- Ensure high quality delivery within expected timelines
Salary according to skills and experience.