Job Summary
We are MHCLG We are looking for two Senior Data Scientists to help transform how the Resilience and Recovery Directorate (RED) uses data, digital services, automation and AI during emergencies that affect communities across England.
When crises happen, decision makers need information they can act on quickly and trust.
The directorate works at the core of government’s resilience system, supporting preparation for and response to incidents such as severe weather, flooding, infrastructure disruption, public health threats and other major emergencies.
This role is about building the technical foundations that help information move quickly from those closest to an incident to the people who need to act on it.
You will join the new Transformation Unit, a multi-disciplinary team focused on building practical systems, tools and workflows that help colleagues, local partners and other government organisations access, share and use information more effectively.
The team's role is not to act as a central analysis function, but to create reusable products and AI-enabled workflows that reduce manual effort, improve situational awareness and make better use of data across the resilience system.
You will work on data science, AI and automation projects that turn promising ideas into reuseable tools and workflows.
This could include helping to structure information from local partners, improve reporting flows, support cross-government data sharing, evaluate AI-enabled workflows, or enable users to understand fast-moving situations more quickly.
If you want to use data science and AI to make a real difference during events of national importance, this role offers the opportunity to do just that while developing your technical skills in a supportive, multi-disciplinary team.
Job Description
- As a Senior Data Scientist, you'll:
- Contribute to the development of data science and AI approaches that help users find, structure, summarise, check or share information more effectively
- Work with colleagues and partners to understand current processes, information flows and user needs
- Build and iterate prototypes, workflows and tools that use data science, large language models, machine learning and automation safely and effectively, working closely with the Senior AI Engineer and wider team
- Experiment with different approaches to ingesting, structuring and reusing information from text, documents, returns and other sources, balancing quality, speed, scalability and cost-effectiveness
- Work with software development, machine learning engineering, delivery and service design colleagues to help move successful prototypes towards services that can be scaled, maintained and improved over time
- Apply good development practices, including clear code, version control, documentation and appropriate monitoring of AI-enabled workflows
- Evaluate AI systems and workflows proportionately, using testing, error analysis, user feedback and monitoring to understand performance, risks, limitations and real-world impact
- Support responsible use of AI by considering privacy, bias, the limits of what these systems can reliably do, and where human oversight is needed
- Explain technical options, evidence, risks and trade-offs clearly to both digital and non-digital colleagues
Person specification
- As a Senior Data Scientist, You'll Have
- Experience using structured and unstructured data with data science, machine learning and large language models to build practical tools, workflows or prototypes
- The ability to identify where data science, AI or automation could reduce manual effort, improve information quality or help people use data more effectively, and to explore these opportunities with technical colleagues
- Curiosity about developments in data science, AI and information-ingestion approaches, and the judgement to identify which emerging tools or techniques are worth testing in a practical delivery context
- Experience writing clear and maintainable Python code, using version control such as Git, and contributing to shared codebases through pull requests, review and feedback
- Evidence of working in an Agile or iterative way, including testing ideas early, learning from users and improving products or workflows over time
- Experience using cloud services such as AWS, Google Cloud Platform or Azure to support data storage, computing or machine learning
- Ability to play your part in emergency response when needed and contribute to RED's 24/7 monitoring for emergencies. Training will be provided and additional compensation is available for any evening or weekend working required