Principal Data Scientist

Elsevier; Greater London; Hybrid; GBP 65,000 - 105,000; Full time

Job summary

Elsevier in London and Amsterdam seeks a Principal Data Science Leader to shape AI strategies across teams, including NLP, generative AI, and RAG systems. You will set technical direction, ensure production readiness, and mentor multiple data science groups.

You will engage with senior stakeholders, translate business priorities into technical roadmaps, oversee governance and model risk, and promote responsible AI practices while delivering high-impact knowledge discovery solutions.

Qualifications

• Significant senior-level data science/AI experience across NLP, information retrieval, or related fields.
• Hands-on AI/ML/NLP, generative AI, and retrieval-based systems with ability to discuss technical details.

Responsibilities

• Set technical direction and architectural standards for AI/ML and NLP solutions across teams.
• Guide integration of metadata, ontologies, and knowledge assets into AI workflows.
• Review code/architecture for production readiness and provide hands-on support when needed.
• Unify technical approaches into shared patterns and libraries.
• Define and maintain shared evaluation and monitoring frameworks.

Skills

Python

LLMs

NLP

RAG search

Leadership

Mentoring

Stakeholder management

Governance & compliance

Communication

Cloud platforms

Tools

Fine-tuning

Evaluation frameworks

Job description

Salary: £65,000 - 105,000 per year

Requirements:

• Significant experience in data science, AI, machine learning, NLP, information retrieval, or a related field, including experience at a senior or principal level.
• Strong hands‑on background building AI/ML, NLP, generative AI, and retrieval‑based systems, with the ability to engage with technical details when required.
• Expertise with LLMs, including fine‑tuning, prompt engineering, grounding strategies, and responsible AI practices.
• Demonstrated experience defining technical standards, evaluation frameworks, or governance processes across teams.
• Working knowledge of AI governance, model risk, and compliance requirements.
• Strong Python skills and solid machine learning fundamentals.
• Experience with large‑scale text or content‑rich datasets and modern AI/ML frameworks.
• Experience with RAG, semantic, vector, or hybrid search, and experimentation approaches that measure user impact.
• Familiarity with cloud platforms and modern software engineering practices.
• Excellent communication and stakeholder management skills, including the ability to represent technical work to senior and non‑technical audiences.
• Strong mentoring and leadership skills, with experience influencing and coordinating across multiple teams.

Responsibilities:

• Set technical direction and architectural standards for AI/ML, NLP, and generative AI solutions across teams, including LLM‑powered workflows, RAG systems, retrieval, ranking, and recommendation capabilities.
• Guide the integration of scientific metadata, ontologies, taxonomies, and knowledge assets into AI workflows, favouring reusable, consistent patterns.
• Review code, architecture, and technical decisions across teams to ensure production readiness, and provide hands‑on support when needed.
• Unify technical approaches into shared patterns, libraries, or frameworks to reduce duplication and divergence across teams.
• Define and maintain shared standards, evaluation, and monitoring frameworks to support consistent quality, trust, and reliability.
• Lead or contribute to AI governance and compliance activities, including responsible AI practices, model risk assessment, and regulatory adherence.
• Conduct or oversee technical reviews and quality audits, identify gaps, and drive remediation.
• Mentor and coach across data science teams to build capability and support consistent, high‑quality delivery.
• Harmonise tooling and delivery practices across distributed teams while supporting team‑level autonomy.
• Represent data science in senior management and governance meetings, communicating strategy, risk, and progress to non‑technical stakeholders.
• Advise senior leadership and translate business priorities into technical direction.
• Collaborate across teams and functions to turn complex, ambiguous challenges into practical solutions.

Technologies:

• AI
• Cloud
• Fine‑tuning
• Support
• LLM
• Machine Learning
• Python
• RAG

More:

We are Elsevier, a global leader in information and analytics. We combine quality information and extensive datasets with analytics to support science and research, health education, interactive learning, and healthcare and clinical practice. Our Data Science Life Sciences team works on generative AI, machine learning, and NLP, developing enrichment pipelines for life sciences products including Reaxys, Embase, and Pharmapendium. In this principal role, you will provide technical and thought leadership across multiple data science teams, shaping advanced AI solutions for knowledge discovery and decision support; hands‑on involvement will be occasional and focused on high‑priority or high‑risk work. We promote work‑life balance and offer wellbeing initiatives, shared parental leave, study assistance, sabbaticals, and location‑specific benefits. Flexible hours are available. The role is listed in London Wall and Amsterdam and is full‑time. For work in Amsterdam, the stated base pay range is 86,900–144,600; the role may be subject to a collective labour agreement in the Netherlands. We are committed to a fair and accessible hiring process and are an equal opportunity employer.

last updated 40 week of 2026