Data Management Specialist

We’re looking for a Data Management Specialist who is passionate about the curation and integration of high quality experimental data to support drug discovery projects.

At IsoLabs you will be a core part of the data team, building our large scale, high quality data asset to power our next generation of groundbreaking AI/ML models. Your role will be to partner directly with discovery project teams to integrate data generated throughout drug design cycles. You will bring domain expertise in discovery data management to co-develop the technical solutions and experimental data workflows we need to accelerate decision making and re-imagine drug discovery.

What you will do 

• Support drug design cycles such that all chemistry and biological assay data necessary to underpin project decision making is efficiently captured and available.
• Streamline experimental assay data integration by developing data capture, analysis, and visualisation workflows.
• Collaborate with internal and external teams to develop data exchange standards and implement user-friendly ELNs that ensure the integrity of ingested data.
• Apply your expertise in compound registration to facilitate effective compound management within internal databases.
• Contribute to the wider data team’s efforts to build a large, diverse, and high quality data asset that powers IsoLabs’ next generation of drug discovery ML models.
• Communicate your work and raise awareness of opportunities to improve data quality.

Skills and qualifications 

Essential:

• Experience working in drug discovery informatics or data management roles for small molecule programs within the pharma/biotech industry.
• BSc, MSc or PhD degree in (bio)chemistry, pharmacology or relevant degree in the life sciences.
• Experience working with a broad range of experimental assay readouts used in the drug discovery process (e.g. in-vitro, biophysical and/or cellular assays; ADMET properties).
• Experience in compound registration and the principles and implementation details of chemical standardisation.
• Good knowledge of ontologies, data management frameworks and the curation of data to adhere to high standards of scientific quality.
• Experience using and configuring an Electronic Lab Notebook (ELN) system and defining robust data exchange standards with third parties.
• Working knowledge of python and SQL and potentially other workflow tools (e.g. Knime) with experience using cheminformatics and data science toolkits (e.g. RDKit, pandas)
• Strong communicator and a proven collaborator with both multi-disciplinary biology/chemistry and product/engineering teams

Nice to have:

• Experience configuring third-party data analysis and visualisation software (e.g DataWarrior, Spotfire, Tableau).
• Knowledge of best practices in data management for biologics.
• Familiarity with data engineering concepts and experience with running jobs on Cloud-based infrastructure.

Hybrid working

It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in).  As an equal opportunities employer, we are committed to building an equal and inclusive team. If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call.