Data Scientist / Engineer - DNA-Encoded Library Technology
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Summary
Builds data-engineering pipelines and analytical tools to interpret large-scale DNA-encoded library (DEL) screening data for small-molecule drug discovery. Core stack: Python and statistical programming, SQL/LIMS, Spotfire/Tableau visualisation, and cheminformatics toolkits like RDKit/OpenEye, deployed on HPC or cloud.
You develop data engineering pipelines and analytical tools to interpret large-scale DNA-encoded library screening data, supporting small-molecule drug discovery.
Your tasks
- Apply statistical methods and predictive models to interpret large-scale DEL screening datasets
- Develop analytical tools and workflows for screening scientists to prioritise compounds
- Design and maintain automated, reproducible data processing and analysis pipelines
- Develop computational workflows and searchable building-block data resources
- Partner with experimental scientists, computational chemists and machine learning teams
- Present analytical results and technical developments to multidisciplinary audiences
- Promote reproducibility, data integrity and robust engineering practices
What you bring
- PhD or M.S. in Bioinformatics, Statistics, Computer Science, Data Science, Cheminformatics, Software Engineering or related field
- Strong software engineering background deploying pipelines at scale in HPC or cloud platforms
- Experience in high-throughput scientific data analysis, DEL selection outputs or NGS processing pipelines
- Strong proficiency in Python and statistical programming
- Expertise in data visualisation frameworks such as Spotfire or Tableau
- Experience with cheminformatics toolkits and laboratory data systems (LIMS, SQL, relational databases)
Conditions
- Option of a permanent position after the assignment if both sides want it
Technologies
- Python
- Spotfire
- Tableau
- RDKit
- OpenEye
- LIMS
- SQL