BenevolentAI is hiring a

R&D Data Management Specialist

London, United Kingdom

We are looking for an individual with a proven track record of integrating biology and chemistry data from a variety of lab-based environments into a centralised data management platform, or someone who is embarking on a career in data management in scientific research.

As a key member of our Data Operations team, you will collaborate closely with Drug Discovery Scientists from in vitro and in vivo Biology, Chemistry, DMPK and Informatics departments to streamline data processes that support our internal candidate-drug programmes in our AI-driven drug discovery pipeline. 

This role is hybrid and can be based from either Cambridge or London.

Responsibilities:

  • Develop data processing workflows for experiment-data, enabling capture, reporting and visualisation
  • Work collaboratively with internal and external teams to develop user friendly Electronic Lab Notebooks to aid data sharing and ensure data integrity standards are maintained
  • Support our ongoing integration of the Dotmatics suite into the Benevolent discovery process
  • Integrate diverse data sources from internal and external origins, including instrument outputs, data analysis programs (e.g., Excel, Prism) and ELNs.
  • Facilitate the integration of compound management, ordering and inventory across our internal and external repositories
  • Support the management of our Dotmatics user licences, platform updates and deliver end user training
  • Champion the assessment of alternative workflows and data interfaces to further improve and reimagine our processes

We are looking for:

  • Experience in Drug Discovery Informatics, relevant degree or MSc/Res qualification in life sciences
  • Industry experience in supporting drug discovery informatics; preferably +2yrs of data management type activities in a drug discovery environment
  • A collaborative working style with good organisation and communication skills
  • An understanding of the challenges of bulk data transfer between systems; cross-platform integration and data warehousing
  • Experience in developing, integrating and improving custom workflows, confident rollout and support to user teams
  • Experience in communicating closely and effectively with multi-disciplinary project teams, to ensure efficient data analysis, assured data quality and smarter data visualisation
  • A track record of understanding the data needs of drug discovery; suggesting innovative solutions to improve data flow, data availability and resolving assay analysis and data integration issues with internal and external teams

Nice to haves:

  • Familiarity with commonly used informatics tools and scientific workflow systems; Pipeline Pilot, Knime 
  • Bonus points for an understanding of programming languages such as SQL, Python and use of Web APIs
  • An understanding and applied business use of Biology and Chemistry ELNs
  • Familiarity with data-management tools; e.g. Dotmatics, Genedata, XLfit, Prism, Tibco Spotfire, CDD Vault, IDBS-ActivityBase
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