Data Scientist

Pearson VUE

Senior Data Scientist leading data science projects and collaborating across teams at Pearson. Focusing on AI and LLM features to enhance learning capabilities with measurable impact.

Posted 6/8/2026full-timeLondon • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSPythonSQL

About the role

Key responsibilities & impact

We’re hiring a senior data scientist to help stand up and scale a shared data science capability that partners with stream-aligned teams.
You’ll report into the Data Science Team Manager and lead end‑to‑end DS/ML projects, shape standards, mentor teammates, and ship models into production, balancing quick wins with robust engineering.
In particular, we are currently exploring ideas around using AI and OCR to process documents and learner work, and to validate marking consistency in a range of qualifications.
Partner with stakeholders across the business to explore high‑impact opportunities.
Own the full lifecycle: problem framing, data discovery, feature engineering, modelling, evaluation, deployment, monitoring, and iteration.
Build and productionize LLM features where appropriate (retrieval‑augmented generation, evaluation, safety guardrails, cost/latency optimization) on AWS.
Contribute to DS/ML standards: experimentation, model governance, documentation, and reproducibility.
Mentor junior scientists, work with external contractors and collaborate closely with data engineering on pipelines and data quality.

Requirements

What you’ll need

A proven track record delivering projects in a Data Science or AI
Experience deploying models to production,understanding of deployment options and trade‑offs.
Practical LLM experience: prompting, fine‑tuning or adapter methods, and building RAG systems.
Orchestration: for example LangChain for pipelines/agents.
RAG best practices and evaluation workflows (e.g., agentic/RAG patterns on SageMaker).
Comfortable choosing the right technique for the job (from baselines to advanced models), with an emphasis on measurable impact and maintainability.
Clear communication with non‑technical partners; ability to translate outcomes to business metrics.
Strong Python for data science and ML; fluency with SQL.
A degree in a relevant discipline, ideally with further post graduate qualification.
Right to work in the UK

Benefits

Comp & perks

Purpose-driven, learner-first; we prize curiosity, decency, and accountability, and we work to ensure everyone belongs and can grow their career.
Collaboration and asynchronous communication are essential.

ATS Keywords

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Hard Skills & Tools

data sciencemachine learningmodel deploymentfeature engineeringevaluationLLMpromptingfine-tuningSQLPython

Soft Skills

mentoringcommunicationcollaborationproblem framingstakeholder engagementtranslating outcomesorganizational skillsleadership

Certifications

degree in relevant disciplinepost graduate qualification