Senior Data Scientist (Band 3/ SEO)

Overview

In this Data Scientist role, you will help advance HSE’s mission to prevent death, injury and ill-health by building robust data sources and NLP-powered tools to synthesise health and safety information. You will join an analytical team collaborating with technical and regulatory specialists to turn multi-source, text-rich data into evidence for decision-making across sectors. The role offers exposure to innovative government work and cross-functional collaboration to protect workers while contributing to an inclusive workplace. A key hook is shaping data-driven insights at scale to support safety outcomes.

Pay / Benefits

• Hybrid working
• Civil Service Pension contributions
• Learning and development tailored to your role
• Flexible working options
• Inclusive and diverse culture
• Annual leave 185 hours (rising to 222) plus public holidays and extra privilege leave

Responsibilities

• Design, develop and refine NLP applications
• Develop and refine analytical data sources to support decision-making
• Create tools to extract, transform and load data from multiple sources
• Collaborate with programme leads and stakeholders to align outputs with user needs
• Present, document and visualise findings for decision-makers
• Contribute to HSE’s overarching data analysis and evidence-generation strategy

Key requirements

• Extensive knowledge of Python and Python text analysis libraries
• Experience designing and executing QA, benchmarking and evaluation frameworks for ML and LLMs
• Experience developing AI workflows
• Previous experience as a text analyst, data scientist or similar
• Experience leading a project team
• Strong ability to communicate to technical and non-technical audiences
• Ability to work within defined deliverables and timeframes
• Proficiency with ML frameworks (PyTorch, Keras, scikit-learn) and integration of open-source models (Hugging Face)

• Clear communication across levels
• Cross-functional collaboration
• Delivery-oriented mindset
• Python; text analysis libraries
• ML frameworks: PyTorch, Keras, scikit-learn
• Open-source models integration: Hugging Face

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