Data Scientist / ML Engineer at Franklin Templeton designing and productionizing machine learning systems for business solutions. Collaborating with teams to deliver scalable and reliable ML solutions.
About the role
- Data Scientist optimizing virtual screening and hit identification for drug discovery at AQEMIA. Leading projects with interdisciplinary teams to integrate computational technologies.
Responsibilities
- You will join the Rocket Launcher team, which is dedicated to hit identification.
- Your role is to optimise virtual screening and hit optimization pipelines using a multidisciplinary approach.
- You’ll collaborate across scientific domains and lead cross-functional projects to integrate cutting-edge computational technologies.
Requirements
- PhD or equivalent with 8+ years in Data Science, Physics, Computational Chemistry, or related fields.
- Strong Python programming skills.
- Deep experience in scientific data analysis, ideally in life sciences.
- Solid understanding of statistical methods and exploratory data analysis.
- Demonstrated experience leading multi-team scientific initiatives.
- **Nice-to-Have:
- Familiarity with tools like RDKit, OpenMM, or SMILES or experience with molecular simulation data.
- Knowledge of high-performance computing or cloud environments.
Benefits
- International Environment : The work language is English - relocation support and French lessons granted if needed.
- Prime Location : Based in central Paris and London (King's Cross) with the possibility of 2 remote days per week.
- Strong Financial Backing : $100M raised from leading European and International investors
Job title
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