Senior Data Scientist II

Description

The role is a Senior Data Scientist position based in London or Oxford, with hybrid working.

It focuses on designing advanced AI systems that speed up scientific discovery and make knowledge easier to reach at scale, using machine learning, NLP and generative AI to build production-ready tools for researchers and professionals.

The team is global and supports electronic health record products used in education, which teach students digital charting and how to document care in a modern clinical setting. The product is stable, and the team works to keep it that way. The team values trust, respect, collaboration, agility and quality.

You will design and deliver AI, NLP and generative AI solutions for knowledge discovery and decision support. The work involves complex scientific data and applying modern machine learning and LLM-based methods to build scalable, reliable systems that users rely on. You will also work with other teams to turn hard problems into practical, production-ready solutions.

Responsibilities

• Design, build and assess AI, machine learning, NLP and generative AI solutions for scientific and knowledge-discovery uses.
• Build LLM-based workflows and retrieval-augmented generation (RAG) systems for search, summarisation, question answering and generating insights backed by evidence.
• Create retrieval, ranking and recommendation tools, along with decision-support features, using current orchestration frameworks and AI methods.
• Bring scientific metadata, ontologies, taxonomies and other knowledge assets into scalable AI workflows.
• Set up solid evaluation, experimentation and monitoring processes that keep quality, trust, performance and reliability in check.
• Write production-quality Python and work with engineering teams to roll out solutions at scale.
• Lead technically and mentor others to help the team deliver well and keep improving.

Requirements

• Practical experience in data science, AI, machine learning, NLP, information retrieval or a related quantitative field.
• Hands-on experience building AI/ML, NLP, generative AI and retrieval systems in applied or product settings.
• Deep experience with LLMs, including fine-tuning, prompt design, grounding approaches and responsible AI practice.
• Strong Python skills and a solid grounding in machine learning fundamentals.
• Experience with large text or content-heavy datasets and current AI/ML frameworks.
• Experience with RAG, semantic, vector or hybrid search, and with experiments and evaluations that measure user impact.
• Familiarity with cloud platforms and modern software engineering practice.
• Strong communication, collaboration and mentoring skills.

Conditions

Hybrid working between London and Oxford.

The company supports a healthy work and life balance, and offers flexible hours, so you can choose when in the day you work to fit your commitments and your most productive times.

Equal opportunity and accessibility: the company is committed to a fair and accessible hiring process and will make adjustments if you ask.

Benefits

• Wellbeing initiatives, shared parental leave, study assistance and sabbaticals to support your current work and long-term goals.
• Country-specific benefits, available by location.