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# Advanced Specialist, Data Scientist

- **Company:** Elspearson
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Data Discovery, Information Engineering, Fraud Prevention and Detection, Python (Programming Language), Feature Engineering, Retrieval-Augmented Generation, Large Language Models, Machine Learning Operations, Asynchronous Programming, Software Version Control
- **Published:** September 21, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/advanced-specialist-data-scientist/47838455

## About the Role

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 haveExperience 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 PearsonPurpose-driven, learner-first; 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.Full timePosting Date: 2026-07-08

## Description

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 doPartner 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.What you'll bringA 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


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