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Data Scientist
Data Scientist (Hybrid: London/Oxford)
Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions?
Would you enjoy turning complex scientific and business challenges into practical, production-ready AI solutions that create real user value?
About Our Team
Our global team supports products in education, electronic health records (EHRs), preparing students for modern clinical documentation. We maintain a stable, high-quality product built on trust, respect, collaboration, agility, and quality.
About the Role
In this Data Scientist position, you’ll design and implement ML, NLP, and generative AI systems that enhance:
- Scientific discovery
- Knowledge extraction
- Decision support
- Intelligent content understanding
You’ll work with large-scale datasets, applying techniques like classification, deep learning, LLMs, and generative AI to solve complex challenges. By collaborating with cross-functional teams, you’ll transform ambiguous requirements into measurable outcomes that empower researchers and improve knowledge usage.
Responsibilities
Core Technical Work
- Design and build ML/NLP/generative AI solutions for:
- Semantic search
- Information retrieval
- Entity extraction
- Knowledge graph construction
- Content classification
- Recommendation systems
- Question answering (QA)
- Evidence-grounded summarisation
- Develop ranking, feature engineering, and fine-tuned embeddings for complex use cases.
- Optimise retrospectively and proactively, ensuring models deliver reliable, high-quality results.
- Work with heterogeneous data (publications, research datasets, citations, ontologies, unstructured text).
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Model Development & Deployment
- Build, evaluate, fine-tune, and integrate LLMs, foundation models, and SLMs (e.g., GPTs, Claude, Gemini).
- Write tested, production-grade Python and contribute reusable data pipelines for preprocessing/inference.
- Implement monitoring, model drift detection, automated retraining, and optimisation protocols.
Collaboration & Communication
- Partner with engineering, UX, product, and domain experts to refine model requirements.
- Translate ambiguous challenges into data-driven solutions, balancing trade-offs effectively.
- Present insights and trade-offs clearly to technical and non-technical stakeholders.
Requirements
- Experience in data science, ML, AI, NLP, or computational statistics.
- Proven expertise using frontier LLMs/LLMs (e.g., OpenAI, Anthropic, Google models), including fine-tuning.
- Advanced Python skills with emphasis on clean, maintainable, and tested code.
- Deep knowledge of:
- Supervised/unsupervised learning
- Feature engineering, model tuning, and evaluation metrics
- Large-scale text/data processing
- Familiarity with tools: Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, Spark, Hugging Face.
- Strong analytical thinking and ability to solve business/technical challenges.
- Excellent collaborator, respected for clarity and empathy across disciplines.
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Work in a Way That Works for You
- Flexible hours: Shape your schedule to match productivity and work-life balance.
- Employee benefits: Extended parental leave, career development support, phippsical health initiatives, and paid sabbaticals.
About Elsevier
We’re a global leader in scientific information and analytics, driving innovation for researchers, educators, and healthcare professionals. Through data-driven tools and AI, we empower discovery, improve equity, and advance sustainability—helping to build a healthier future for society.
Ready to shape the next generation of AI-driven science? Join us.
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