Senior Data Scientist

Senior Data Scientist – AI/ML (CADD)

I’m supporting an innovative client at the forefront of chemistry, robotics, and AI who is looking to hire a Senior AI/ML Data Scientist to help advance their small-molecule discovery and computer-aided drug design (CADD) capabilities.

This is an opportunity to join a cutting-edge multidisciplinary team and play a key role in building and deploying state-of-the-art models that directly accelerate drug discovery. Open to candidates within the UK/EU/US!

The Role

As Senior Data Scientist, you will:

• Develop and optimise advanced generative models (Transformers, GNNs, Diffusion Models) for molecular design and prediction tasks.
• Build scalable pipelines for processing large chemical/biological datasets and training high-performance models.
• Apply modern AI/ML techniques to challenges such as ADMET/QSAR prediction, reaction prediction, binding affinity, and synthetic route design.
• Work closely with computational chemists, medicinal chemists, and engineers to integrate AI results into real discovery workflows.
• Design robust experiments to ensure model quality, synthesizability, novelty, and accuracy.
• Clearly communicate insights and recommendations across technical and non-technical teams.
• Stay up to date with AI for drug discovery, multimodal models, and emerging research.

What We’re Looking For

• MSc/PhD plus 5+ years of experience in Machine Learning, Computer Science, Computational Chemistry/Biology, or related fields.
• Strong proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
• Deep understanding of modern ML architectures: Transformers, GNNs, VAEs/GANs/Diffusion Models.
• Experience leading complex ML projects end-to-end in a scientific context.
• Track record working with molecular data (SMILES, 3D structures) and biological datasets (protein sequences, assay data).
• Familiarity with efficient training methods (LoRA, quantization, distillation) and GPU/distributed environments.
• Experience with ML for protein structures or small-molecule interactions is highly valuable.
• Strong communication, problem-solving abilities, and a collaborative mindset.

Nice-to-Have Experience

• Cheminformatics tools such as RDKit
• RAG systems and vector databases (FAISS, Pinecone, Milvus, Redis)
• Protein language models (ESM, ProtBERT) or structure prediction approaches
• Synthetic route evaluation frameworks
• SQL/NoSQL databases
• Open-source contributions or project portfolio