Job summary
- Main area
- AI
- Grade
- Civil Service: Grade 7
- Contract
- Permanent
- Hours
- Full time
- Part time
- Job share
- Flexible working
- Job ref
- 919-CA-62445678-EXT
- Employer
- UK Health Security Agency
- Employer type
- Public (Non NHS)
- Site
- Any Core HQ
- Town
- Birmingham / Leeds / Liverpool / London (Canary Wharf)
- Salary
- £56,185 - £70,566 per annum pro rata National(£56,185-66,581)London(£58,340-70,566)
- Salary period
- Yearly
- Closing
- 20/07/2026 23:59
Employer heading
AI & Systems Modeller
Civil Service: Grade 7
Job overview
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 AIgenerated 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.
Main duties of the job
- Operationalise and Design AI/ML Models to Enhance Decision Support
- Validate and Monitor Model Performance
- Integrate Data and Knowledge Sources
Working for our 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. Please visit our careers site for more information https://gov.uk/ukhsa/careers
Detailed job description and main responsibilities
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.
The above provides an outline of the tasks, responsibility and outcomes required of the role. The job description and person specification may be reviewed on an ongoing basis in accordance with the changing needs of the team, Directorate and the Organisation.
Essential role criteria
- Data engineering skills and expertise and experience of low code/coding (e.g. SQL)
- Experience building and deploying AI/ML models, preferably in a finance or enterprise analytics context.
- 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: pl
-
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
Selection Process Details
This vacancy is using Success Profiles and will assess your Behaviours and 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 email us your CV.
Longlisting
In the event of a large number of applications we will longlist into 3 piles of:
-
Meets all essential criteria
-
Meets some essential criteria
-
Meets no essential criteria
If used, the pile(s) ‘Meets all essential criteria’ and ‘Meets some essential criteria’ will proceed to shortlisting.
Shortlisting
In the event of a large number of applications we may conduct an initial sift, on the lead criteria of :
- Data engineering skills and expertise and experience of low code/coding (e.g. SQL).
-
Experience building and deploying AI/ML models, preferably in a finance or enterprise analytics conte
Desirable criteria may be used in the event of a large number of applications/successful candidates.
If you are successful at this stage, you will progress to interview & assessment.
Feedback will not be provided at this stage.
Stage 2: Interview
You will be invited to a ( single ) face to face interview. In exceptional circumstances, we may be able to offer a remote interview.
Behaviours, Ability, Experience, Technical skills will be tested at interview.
Behaviours :
- Changing and Improving (Lead)
- Making Effective Decisions
- Communication and Influencing
- Working Together
- Managing a Quality Service
There will be a Presentation aimed to assess your technical skills. The topic will be : Provide an example of where you have developed a business solution using Machine Learning? What was the situation, what solution did you
implement and why? What was the result?
Interviews dates to be confirmed.
Once this job has closed, the job advert will no longer be available. You may want to save a copy for your records.
Eligibility Criteria - External
Open to all external applicants (anyone) from outside the Civil Service (including internal applicants).
Location - Any Core HQ
This role is being offered as hybrid working based at any of our Core HQs. We offer great flexible working opportunities at UKHSA and operate using a hybrid working model where business needs allow. This provides us with greater flexibility about how and where we work, to get the best from our workforce. As a hybrid worker, you will be expected to spend a minimum of 60% of your contractual working hours (approximately 3 days a week pro rata, (averaged over a month) working at one of UKHSA's core HQs (Birmingham, Leeds, Liverpool, and London). Our core HQ offices are modern and newly refurbished with excellent city centre transport links and benefit from co-location with other government departments such as the Department for Health and Social Care (DHSC).
Salary Information
Please be aware that the salary is based on the office location.
Grade 7
- £56,185- £66,581 (National)
- £58,340- £68,574 (Outer London)
- £60,494- £70,566 (Inner London)
If you are successful at interview, and are moving from another government department, NHS, or Local Authority, the relevant starting salary principles for level transfers or promotions will apply. Otherwise, roles are offered at the pay scale minimum for the grade, but in exceptional circumstances there may be flexibility if you are able to demonstrate you are already in receipt of an existing, higher salary.
Pay increases are through the relevant annual pay award for the role and terms.
Security Clearance Level Requirement
Successful candidates must pass a basic disclosure and barring security check before they can be appointed.
Successful candidates must meet the security requirements before they can be appointed. The level of security needed is:
- Baseline Personnel Security Standard
- Security Clearance
For meaningful National Security Vetting checks to be carried out individuals need to have lived in the UK for a sufficient period of time. You should normally have been resident in the United Kingdom for the last 5 as the role requires Security Check (SC). UK residency less than the outlined periods may not necessarily bar you from gaining national security vetting and applicants should contact the Vacancy Holder/Recruiting Manager listed in the advert for further advice.
Please note: The Chief Operating Officer (COO) group, where this role sits, is undergoing organisational change over the next 12–18 months. While the process is still in the planning stage, some roles may be affected by future restructuring. We are committed to keeping candidates informed and will share updates as they become available.
Person specification
Application Form and Supporting Statement
Essential criteria
- Application Form and Supporting Statement
Interview - Behaviours
Essential criteria
- Changing and Improving
- Making Effective Decisions
- Communication and Influencing
- Working Together
- Managing a Quality Service
Interview - Presentation
Essential criteria
- Presentation
Employer certification / accreditation badges
Documents to download
Further details / informal visits contact
- Name
- Conny Agyei
- Job title
- Resourcing Officer
- Email address
- [email protected]
- Additional information
For information regarding the role please contact [email protected] ( Jayesh Patel - Deputy Director )
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