Senior Python Engineer (Cheminformatics / Drug Discovery)
EPAM is seeking a highly skilled Senior Python Engineer with expertise in Cheminformatics and Computational Chemistry to join our Life Sciences practice.
In this role, you will contribute to the development of advanced software solutions supporting drug discovery and pharmaceutical research. You will work at the intersection of chemistry, data science, and machine learning, building scalable computational tools used by scientists and researchers worldwide.
This position requires strong technical engineering skills combined with deep domain understanding in chemistry or related scientific disciplines.
Responsibilities
- Design and develop software solutions for drug discovery and chemical data analysis
- Build and maintain computational pipelines for processing molecular and experimental data
- Implement algorithms for virtual screening, QSAR/SAR modeling, and molecular descriptor calculation
- Work with chemical structure representations (SMILES, molecular graphs, fingerprints)
- Integrate and analyze data from chemical databases such as ChEMBL and PubChem
- Apply machine learning techniques to chemical and biological datasets
- Collaborate with scientists, researchers, and cross-functional engineering teams
- Ensure code quality, scalability, and reproducibility of computational workflows
Requirements
- Strong Python development experience
- Proven experience in Cheminformatics, Computational Chemistry, or Drug Discovery
- Experience working with QSAR/SAR models, virtual screening, or molecular modeling
- Understanding of chemical structure representation and similarity search
- Experience working with chemical databases (e.g., ChEMBL, PubChem)
- Solid knowledge of data analysis and statistical modeling
- Experience applying Machine Learning techniques in scientific contexts
- Familiarity with tools such as RDKit or similar cheminformatics libraries
- Ability to work in an R&D-oriented environment
Nice to have
- Experience with molecular dynamics simulations
- Knowledge of quantum mechanics modeling
- Experience with cloud environments (AWS, Azure, or GCP)
- Experience deploying ML models into production
- Background in Pharmaceutical or Biotechnology industry
