Data Scientist

Senior Data Scientist - Enterprise Learning & Skills (ELS) Pearson

About Pearson and ELS

Pearson is the worlds learning company; our mission is to help people make progress in their lives through learning. Youll join the Enterprise Learning & Skills (ELS) area supporting the understanding and development of skills in a range of contexts.

Our culture emphasizes belonging diverse viewpoints and a supportive environment where people can do their best work.

The role

Were hiring a senior data scientist to help stand up and scale a shared data science capability that partners with stream-aligned teams.

Youll report into the Data Science Team Manager and lead endtoend 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 handson work across classical ML and modern LLM/RAG systems using services like Amazon SageMaker and Bedrock.

What youll do

• Partner with stakeholders across the business to explore highimpact opportunities.
• Own the full lifecycle: problem framing data discovery feature engineering modelling evaluation deployment monitoring and iteration.
• Build and productionize LLM features where appropriate (retrievalaugmented 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.

What youll bring

• A proven track record delivering projects in a Data Science or AI
• Experience deploying models to productionunderstanding of deployment options and tradeoffs.
• Practical LLM experience: prompting finetuning 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 nontechnical 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.

How we work at Pearson

Purposedriven learnerfirst; we prize curiosity decency and accountability and we work to ensure everyone belongs and can grow their career.

ELS roles span multiple geographies and partner teams; collaboration and asynchronous communication are essential.

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