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 state-of-the-art machine learning and use technologies 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, they 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 their 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, differing 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 of scientific, engineering, and client engagement. You will define the data protocols, harden them with robust validators, integrate them into their 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 their partners. Communicate with big pharma teams and walk them through how things work.
- Manage the small-molecule pipeline using RDKit.
- Curate and standardize major public binding-data corpora (e.g., ChEMBL, BindingDB, PubChem).
Requirements for the role:
- Masters or PhD in Computational Chemistry.
- Highly fluent in Python and RDKit.
- Strong experience within Drug Discovery.
- Hands-on experience curating quantitative binding assay data (KD, Ki, IC50, pIC50).
- Write clean, production-grade code, utilizing version control, modular architectures, and thorough testing.
- 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 flexible hours).
- Comprehensive wellbeing, mental health, and learning budgets.
- 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.
If you like the sound of the Cheminformatician, Client Facing, | AI Pharma, B2B, Drug Discovery | Fully Remote (UK/EU), Up to £110,000 + Stocks & Benefits - Drop them over your CV and they will give you a call if they think you are a good fit.
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