Owen Thomas | B Corp™
Cheminformatician, Client Facing, | AI Pharma, B2B, Drug Discovery | Fully Remote (UK/EU), Up to £110,000 +Stocks& Benefits
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Cheminformatician, Client Facing, | AI Pharma, B2B, Drug Discovery | Fully Remote (UK/EU), Up to £110,000 +Stocks& Benefits
Cheminformatician, Client Facing, | AI Pharma, B2B, Drug Discovery | Fully Remote (UK/EU), Up to £110,000 +Stocks& Benefits
About the Company We are working with a venture backed biotech scale up company who are tech transforming how artificial intelligence is applied to pharmaceutical R&D and drug discovery. They build start of the art machine learning and use technlogies such as federated learning to apply ML onto big pharma data
Their hosts secure distributed data networks for drug discovery AI, spanning structural biology, co-folding, ADMET, and antibody developability. By allowing models to be trained safely across disparate, proprietary industry datasets, we help partners unlock superior predictive performance while keeping their intellectual property fully protected
About the Role We are seeking a Cheminformatician to own how biological binding data is prepared, standardised, and scaled across our collaborative networks.
Binding data is the critical input that determines whether their co-folding and binding-affinity models perform in real-world drug programs. Because this data arrives from various pharmaceutical partners in highly heterogeneous shapes. It differs by assay registry, schema, metadata, and chemical representation standards. They need an expert who can turn chaos into a repeatable, production-grade data pipeline.
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This role is a unique mix scientific, engineering and client engagement. You will define the data protocols, harden them with robust validators, integrate them into our core product, and collaborate directly with partner scientists to unblock data retrieval.
What You Will Be Doing: Define and maintain the binding-data preparation protocol, including data schemas, small-molecule standardisation, assay metadata models, and the handling of varied values (KD, Ki, IC50, pIC50), qualifiers, and replicate aggregations. Develop modular Python scripts, robust validators with actionable error logging, and reusable pipelines capable of ingesting data from diverse upstream pharma systems Act as the technical bridge to our partners. Communicate with big pharma teams and walk them through how thingswork. Manage the small-molecule pipeline using RDKitCurate and standardize major public binding-data corpora (e.g., ChEMBL, BindingDB, PubChem)
Requirements for the role: Masters or PHD in Computational Chemistry. You are highly fluent in Python andRDKit. Strong experience within Drug Discovery. You have hands-on experience curating quantitative binding assay data (KD, Ki, IC50,pIC50) You write clean, production-grade code, utilizing version control, modular architectures, and thorough testing. You are comfortable with client facing aspects of the role.
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Bonus Points: Practical familiarity with the nuances and hidden pitfalls of public data sources like ChEMBL, BindingDB, and PubChem. Experience leveraging modern LLM tooling to accelerate metadata harmonization or data cleaning. Experience working across institutional data boundaries (e.g., federated learning or privacy-preserving data networks) where data visibility is partial or restricted.
What They Offer
Up to £110,000 plus early-stage equity/virtual share options. A remote-first working culture (+ or - 2 hours of EU with flexiblehours.) Comprehensive wellbeing, mental health, and learningbudgets. Generous annual leave allowance. Regular international team retreats and company offsites. The opportunity to work alongside a high-calibre, execution-focused team out of top-tier tech and biotech organisations.
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