Senior Data Scientist, NLP, Applied AI

Wiley

. Design and build NLP enrichment pipelines extracting entities, classifications, claims, and summaries from scientific full-text at scale .

Posted 11/2/2026full-timeRemote • United Kingdom, Canada, United States, Austria, Czechia, Denmark, France, Greece, Italy, Netherlands, Romania, SpainSenior💰 £51,100 - £73,167 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building NLP enrichment pipelines, with a strong focus on LLMs, transformers, and evaluation metrics. Capable of translating stakeholder feedback into actionable modeling work while managing end-to-end production releases.

Highest-signal resume keywords

NLP BackgroundPython SkillsModel Evaluation ExperienceAWS FamiliarityAgentic AI Exposure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

NLPLLMsTransformersEmbeddingsNERClassificationSequence LabelingModel EvaluationCost EstimatesOperational Tradeoffs

Soft Skills

CollaborationStakeholder CommunicationJustification of Choices

Tools & Technologies

AWSS3BatchLambdaSageMakerParquetIceberg

Industry Keywords

Scientific TextScholarly TextAgentic AI ApplicationsMulti-Step ReasoningTrajectory Evaluation

Tech Stack

Tools & technologies

AWSPython

About the role

Key responsibilities & impact

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
Select approaches based on evaluation, cost, and operational tradeoffs
Build golden evaluation sets in consultation with subject-matter experts and vendors
Choose evaluation metrics and balance speed, quality, and cost
Contribute to agentic AI applications that reason over enriched scientific corpora
Shape how agents ground and defend their answers
Work directly with editors, product managers, and engineers
Translate stakeholder feedback into concrete modeling work
Own models, evaluations, code, production releases, and outcomes end to end

Requirements

What you’ll need

Strong NLP background across LLMs, transformers, embeddings, retrieval, NER, classification, and sequence labeling
Experience building evaluations and learning from results
Strong Python skills
Comfort working in exploratory notebooks and production repositories
Ability to compare modeling approaches and justify choices using evaluations, cost estimates, and operational tradeoffs
Experience working with scientific or scholarly text (nice to have)
Familiarity with AWS, including S3, Batch, Lambda, and 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, including tool use, multi-step reasoning, guardrails, and trajectory evaluation (nice to have)
Resume/CV required when applying

Benefits

Comp & perks

Meeting-free Friday afternoons
Professional development opportunities
Employee programs supporting community, learning, and growth
Comprehensive benefits package
Equal opportunity and affirmative action employer
Reasonable accommodation for applicants and employees with disabilities