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Principal Cheminformatics Data Scientist
2 months ago
We are seeking a highly experienced Senior Principal Cheminformatics Data Scientist to join our Cheminformatics & Computational Chemistry team at BenevolentAI. As a key member of our team, you will play a significant leadership role in advancing our small molecule drug discovery programmes.
Key Responsibilities- Lead Cheminformatics Support: Provide expert cheminformatics and computational modelling support for multiple drug discovery projects, working closely with medicinal and computational chemists, and the rest of the project team.
- Drive Innovation: Work with the team to identify and develop innovative approaches to expand our cheminformatics capabilities, and drive the long-term strategic thinking of the team.
- Computer-Aided Drug Design: Apply a wide range of computer-aided drug design techniques to identify and develop small molecules, including virtual screening, reaction and fragment enumeration, de novo design, and chemical library design and sampling.
- Data Analysis and Reporting: Gather, analyse and report on biochemical data from a range of data sources to derive novel insights into SAR and SPR, including the manipulation and analysis of biochemical data at scale.
- QSAR Modelling: Build, evaluate and deliver QSAR models to advance our small molecule Drug Discovery programmes, and to support their use by project teams.
- Process Development: Develop processes, customisable workflows and computational techniques that can be adapted and applied across the drug discovery portfolio.
- Domain Expertise: Act as the key domain expert for cheminformatics and the handling of biochemical data, and consult with scientific and engineering teams from across BenevolentAI.
- Team Leadership: Line-manage a portion of the team, defining and monitoring their individual goals, in line with company and department objectives, and conduct performance reviews.
- Talent Development: Nurture talent at BenevolentAI by supporting junior members of the team in their working, sharing your experience and providing a mentoring role.
- PhD or Equivalent: PhD or equivalent in Cheminformatics, Computational Chemistry, Molecular Modelling or a closely related field and extensive experience of computer-aided drug discovery in pharma, biotech or academic drug discovery unit.
- Cheminformatics Expertise: Detailed demonstrable knowledge of a wide range of cheminformatics approaches and their application to live drug discovery projects, and the ability to objectively design scientifically-merited experiments.
- Computer-Aided Drug Design: Extensive practical experience of computer-aided drug design, such as compound library design, similarity and substructure searching, virtual screening, reaction enumeration, molecular fragmentation, R-group analysis and combinatorics, multi-parameter optimisation.
- Machine Learning and QSAR Modelling: Practical experience in developing, deploying and applying machine learning and QSAR modelling techniques to chemical and biological data, and knowledge of a wide range of chemical featurisers, and a strong understanding of best practices.
- Data Processing: Extensive experience processing chemical and biological data from a range of data sources, e.g. ChEMBL, SureChEMBL, and PubChem.
- Programming and Technical Skills: Strong and demonstrable programming and technical skills, and familiar with open source and proprietary cheminformatics libraries e.g. RDKit or other leading industry toolkits.
- Innovation and Leadership: Innovator of new ideas and approaches in the cheminformatics and computational chemistry fields of research, as demonstrated by appropriate papers, presentations, or code contributions to open source projects.
- Communication and Leadership: Excellent communication and leadership skills, especially when working with junior colleagues from a range of technical and scientific backgrounds.
