Principal Data Scientist, NLP, Applied AI

🔥 0 minutes ago

🇬🇧 United Kingdom – Remote

💵 £67.7k - £96.9k / year

⏰ Full Time

🔴 Lead

📊 Data Scientist

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Wiley

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

📚 Education

🔬 Science

Education • Science

Wiley is a global publishing and information services company that connects researchers, educators, students, and professionals through scholarly journals, books, digital content, and learning platforms. It operates Wiley Online Library with thousands of journals, reference works, and books, provides textbooks and courseware (including rental and digital access), and offers publishing, research support, and AI-enabled tools and services for academic institutions, R&D teams, societies, and corporations. Wiley advances research discovery and professional learning by combining trusted content with technology platforms, licensing, and development services.

📋 Description

• Design and build NLP enrichment pipelines extracting entities, classifications, claims, and summaries from scientific full-text at scale • Compare traditional NLP, embedding-based retrieval, LLM prompting, and fine-tuned smaller models for extraction and enrichment • Own evaluation by building golden sets, choosing metrics, and balancing speed, quality, and cost • Write production-quality Python and manage concurrency and cost for high-volume LLM workloads • Collaborate with data engineers to orchestrate work in Airflow, Dagster, and data build tools • Design idempotent, retryable, and evaluable pipeline stages • Contribute to agentic AI applications that reason over enriched scientific corpora • Collaborate with editors, product managers, and engineers to inform product decisions and translate stakeholder feedback into modeling work

🎯 Requirements

• Deep Python experience in production and at scale • Strong NLP background across LLMs, transformers, embeddings, retrieval, NER, classification, and sequence labeling • Experience building evaluations and learning from results • Ability to compare approaches using evaluation, cost, and operational tradeoffs • Track record of shipping production systems that deliver value to real users • Nice to have: experience with scientific or scholarly text • Nice to have: familiarity with AWS (S3, Batch, Lambda, SageMaker) • Nice to have: familiarity with Parquet or Iceberg data lake patterns • Nice to have: experience running LLMs under production cost and latency budgets • Nice to have: exposure to agentic AI applications, tool use, multi-step reasoning, guardrails, and trajectory evaluation

🏖️ Benefits

• Meeting-free Friday afternoons • Professional development opportunities • Robust employee programming to foster community, learn, and grow • Comprehensive benefits package • Reasonable accommodation for applicants and employees with disabilities

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