Oliver Bernard
Data Scientist – Scientific Research - Hybrid, London
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Data Scientist – Scientific Research - Hybrid, London
Central London | Hybrid working | Up to £70k + bonus
Use data and AI to accelerate scientific discovery!!
We're working with a global technology and information business helping researchers, healthcare professionals, and organisations make better decisions through trusted scientific content, data, and advanced analytics.
We're now looking for a Data Scientist to join a growing data science organisation and work on challenging problems across machine learning, NLP, information retrieval, and generative AI.
What you'll be doing
- Develop and deploy machine learning and AI solutions across search, discovery, recommendation, and knowledge applications.
- Develop NLP and LLM-based solutions, including embeddings, semantic search, RAG, and generative AI applications.
- Build and evaluate models using Python, SQL, and modern ML frameworks such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
- Communicate findings clearly to technical and non-technical stakeholders and help translate ambiguous problems into practical data science solutions.
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You'll ideally have:
- Strong Python and SQL skills.
- Solid understanding of machine learning fundamentals, including model development, feature engineering, experimentation, and evaluation.
- Experience working with large-scale datasets and production data science workflows.
- Practical experience with NLP, information retrieval, recommendation systems, or generative AI.
- Experience with tools such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, Pandas, and NumPy.
- Experience working with APIs, data pipelines, and deploying models into production.
- Strong statistical and analytical skills, with the ability to design robust experiments and interpret results.
- A degree in Data Science, Computer Science, Statistics, Mathematics, or another quantitative discipline is advantageous but not essential.
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Central London | Hybrid working | Up to £70k + bonus
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