AI & Systems Modeller

Any Core HQ : Birmingham(23 Stephenson Street) , Leeds(Quarry House), Liverpool(Cunard Building), London(10SC, Canary Wharf)

Job Summary The AI &​ Systems modeller is the owner of the algorithms that form the foundation of finance insights. In this role, you will ensure business users have seamless access to actionable intelligence with limited human intervention. You will champion an 'Expert-in-the-loop' (HITL) methodology, ensuring that AI generated insights are validated by financial subject matter experts to combine statistical precision with institutional knowledge. You will create, maintain, monitor, and adjust AI and machine learning (ML) -based systems and establish automated frameworks that underpin analytic tools, deploying sophisticated analytics at scale and enabling data-driven decision making.You will collaborate with product managers and cross-functional teams to assist in building user-centric AI capabilities integrated into core finance processes.

Your role will help the organisation shift from routine analysis to continuous model enhancement and decision enablement. You will define, track, and communicate the business value generated by deployed models, including improvements in forecast accuracy, cost savings, and decision cycle reduction.

To be successful in this role, you must bring a strong blend of data science expertise, technological proficiency, and financial acumen. This position offers a unique opportunity to shape the future of analysis and performance in a tech-first, analytics-driven finance function.

Working for your organisation

We pride ourselves as being an employer of choice, where Everyone Matters promoting equality of opportunity to actively encourage applications from everyone, including groups currently underrepresented in our workforce.

UKHSA ethos is to be an inclusive organisation for all our staff and stakeholders. To create, nurture and sustain an inclusive culture, where differences drive innovative solutions to meet the needs of our workforce and wider communities. We do this through celebrating and protecting differences by removing barriers and promoting equity and equality of opportunity for all.

Job Description

• Operationalise and Design AI/ML Models to Enhance Decision Support
• Validate and Monitor Model Performance
• Integrate Data and Knowledge Sources

Operationalise And Design AI/ML Models To Enhance Decision Support :**

• Design and develop models that directly address key business challenges, delivering clear, actionable insights that support financial decisions and improved operations. Occasionally, conduct ad hoc analyses to address urgent business needs.
• Ensure seamless integration and embedding of AI/ML solutions with core finance planning and analytics platforms and next-generation data architectures to enable scalable, real-time decision support, replacing manual processes and static reporting within core workflows.
• Deliver model outputs through intuitive, user-facing tools (to empower real-time, self-service analytics across finance and business functions, enabling decision making at scale.
• Leverage modern MLOps practices such as versioning, performance monitoring, and automated retraining pipelines to ensure models remain scalable, relevant, and operationally excellent.
• Apply advanced techniques such as supervised and unsupervised learning, reinforcement learning (RL), generative modeling, and feature engineering to build scalable models.
• Design automated variance analysis loops that systematically compare generated forecasts against financial quarter/annual closed actuals. Use these variance outputs to identify error patterns and trigger back-feeds for model retraining.

Validate And Monitor Model Performance:

• Conduct rigorous testing and validation of models using metrics such as accuracy, precision, recall, and cross-validation against business KPIs, A/B testing, and Explainable AI to ensure reliability and transparency.
• Validate the integrity of fully automated data pipelines. Promptly identify and report any data quality issues or anomalies to maintain compliance with governance standards.
• Proactively monitor and improve model performance against defined business KPIs, identifying improvement areas to optimise performance and reliability. Additionally, track and report adoption KPIs for model outputs to lead targeted enablement and drive iterative enhancements, maximizing business value realisation and user satisfaction.
• Leverage modern MLOps practices to detect Data Drift and Concept Drift early. Establish automated triggers that initiate retraining pipelines when model variance against actual financial data exceeds defined thresholds.
• Ensure models adhere to AI governance policies, regulatory standards, and ethical guidelines, including bias mitigation and explainability.
• Implement model risk controls, maintain audit trails, and ensure documentation supports auditability and compliance with evolving regulatory requirements.

Integrate Data And Knowledge Sources:

• Integrate diverse data sources into model pipelines, including structured, unstructured, and tacit knowledge.
• Identify potentially valuable new data sources and evaluate their impact on model performance through exploratory testing and validation, ensuring any additions enhance predictive accuracy and align with governance standards.
• Partner with data architects to design conceptual and physical data models, ensure end-to-end data lineage, and uphold robust data governance across all model inputs and outputs.
• Support training and enablement efforts to help users effectively engage with model-driven tools.
• Operationalise and Design AI/ML Models to Enhance Decision Support
• Validate and Monitor Model Performance
• Integrate Data and Knowledge Sources

Integrate Data And Knowledge Sources:

• Integrate diverse data sources into model pipelines, including structured, unstructured, and tacit knowledge.
• Identify potentially valuable new data sources and evaluate their impact on model performance through exploratory testing and validation, ensuring any additions enhance predictive accuracy and align with governance standards.
• Partner with data architects to design conceptual and physical data models, ensure end-to-end data lineage, and uphold robust data governance across all model inputs and outputs.
• Support training and enablement efforts to help users effectively engage with model-driven tools.

Person specification

Essential Role Criteria

• Data engineering skills and expertise and experience of low code/coding (e.g. SQL)
• Experience designing feedback systems where actuals (ground truth) are automatically fed back to update model weights. Understanding of Model Drift (detecting when financial patterns shift) and strategies to mitigate it.
• Demonstrable experience with large-scale datasets and machine learning.
• Proven ability to adapt models to evolving business needs and regulatory requirements and be able to demonstrate proactive approach to maintaining up-to-date understanding and translation of complex information and practical guidance.

Desirable Role Criteria:

• Demonstrated success in developing and maintaining models for forecasting, risk assessment, scenario planning, or decision support.
• Knowledge of Reinforcement Learning agents and their application in optimization problems.
• Experience with Active Learning workflows, where human expert feedback is captured to retrain models.
• Experience working with cross-functional teams, including finance, IT, and compliance, to co-create solutions that address finance challenges.
• Familiarity with Oracle Cloud platform

Alongside your salary of £56,185, UK Health Security Agency contributes £16,276 towards you being a member of the Civil Service Defined Benefit Pension scheme. Find out what benefits a Civil Service Pension provides (opens in a new window).

• Learning and development tailored to your role
• An environment with flexible working options
• A culture encouraging inclusion and diversity
• A Civil Service pension with an employer contribution of 28.97%

Artificial intelligence

Artificial intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our candidate guidance (opens in a new window) for more information on appropriate and inappropriate use.

Selection process details

This vacancy is using Success Profiles and will assess your Behaviours/Ability/ Experience/Technical skills.

Stage 1: Application &​ Sift You Will Be Required To Complete An Application Form. You Will Be Assessed On The Listed Essential Criteria, And This Will Be In The Form Of A:

• Application form (‘Employer/ Activity history’ section on the application)
• 1,000 word Supporting Statement

Healthjobs UK has a word limit of 1, 500 but your supporting statement must be no more than 1,000 words. We will not consider any words over 1,000 words. This should outline how you consider your skills, experience and knowledge provide evidence of your suitability for the role, with reference to the essential criteria.

You will receive a joint score for your application form and statement. The application form is the kind of information you would put into your CV. Please be advised you will not be able to upload your CV. Please complete the application form in as much detail as possible. Please do not em