Develop, run and evaluate virtual screening pipelines which allow Aqemia to identify promising chemical starting points.
Develop, run and evaluate hit expansion and hit-to-lead pipelines which allow Aqemia to improve chemical starting points obtained during the phase of virtual screening.
Contribute to interdisciplinary projects across physics, chemistry, data science, and ML teams.
Apply in-depth statistical (for instance bayesian optimization) and exploratory research data analyses to improve pipeline performance.
Contribute to identify technical gaps and develop custom solutions.
Stay current on scientific literature and recommend improvements in virtual screening and hit optimization.

MSc (at least 3 years of experience after MSc) or PhD in Data Science, Statistics, Computer Science, or related fields.
You are proficient in python or other object-oriented programming languages.
Proven experience in scientific data analysis, ideally in life sciences.
Proven understanding of statistical methods and exploratory research data analysis.
You have excellent written and verbal communication skills, paired with a strong intellectual curiosity and the ability to quickly absorb new frameworks.
Bayesian optimization is a plus.
Experience with Cloud technologies is a plus.
Experience with large datasets is a plus.

Prime Location with Flexibility : Our offices are located in the heart of Paris and London (King’s Cross), with flexible work arrangements including up to two remote days per week.
Strong Financial Backing : $100M raised from leading European and International investors

Data Scientist

Key skills