Advanced Specialist, Data Scientist

The role

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. Tech focus: Python and AWS (or equivalents in Azure or GCP), with hands‑on work across classical ML and modern LLM/RAG systems using services like Amazon SageMaker and Bedrock.

What you’ll do

• 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 productionise LLM features where appropriate (retrieval‑augmented generation, evaluation, safety guardrails, cost/latency optimisation) 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.

What you’ll bring

• A proven track record delivering projects in a Data Science or AI
• Experience deploying models to production, with an 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.

Nice to have

Experience in one or more of our domains (assessment/psychometrics, workforce skills/ontologies, recommendations, fraud detection).

Familiarity with MLOps practices (CI/CD for ML, experiment tracking, data/version control) in a cloud environment.

Location and Work Arrangement

This is a hybrid role, located in Central London, with an expectation of 1-2 days in the office each week.

EEO Statement

Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing TalentExperienceGlobalTeam@grp.pearson.com.

Job Family

TECHNOLOGY