At a Glance
- Tasks: Lead exciting data science projects and mentor teammates while using cutting-edge AI technologies.
- Company: Join Pearson, a forward-thinking company dedicated to innovation in education.
- Benefits: Enjoy a hybrid work environment, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with diverse teams in a dynamic, inclusive workplace.
- Why this job: Make a real impact by shaping the future of learning through data science.
- Qualifications: Experience in data science, strong Python skills, and a degree in a relevant field.
The predicted salary is between 70000 - 90000 £ per year.
Role Overview 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 Sage Maker and Bedrock.
Responsibilities 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.
Qualifications A proven track record delivering projects in a Data Science or AI role, deploying models to production, and understanding deployment options and trade‑offs.
Practical LLM experience: prompting, fine‑tuning or adapter methods, and building RAG systems.
Orchestration experience, for example Lang Chain for pipelines/agents.
RAG best practices and evaluation workflows (e. g., agentic/RAG patterns on Sage Maker).
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 and the 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 postgraduate 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.
Work Environment Hybrid role located in Central London.
Expectation of 1‑2 days in the office each week.
Equal Opportunity Employer 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 Talent Experience Global Team@grp. pearson. com. #J-18808-Ljbffr
