Trac proudly powers the recruitment for

NHS Counter Fraud Authority

About

The NHS Counter Fraud Authority (NHSCFA) is the national body responsible all for matters relating to the prevention, detection and investigation of economic crime across the NHS. Aligned to the DH Health Group Counter Fraud strategy, the NHSCFA acts as the principal lead for the NHS and wider health group in counter fraud intelligence work.

Contact

Address
NHS Counter Fraud Authority
7th Floor,
10 South Colonnade,
London
E14 4QQ
Contact Number
0300 330 0739

Find out more

Jobs Website

Login changes are coming

From July 2025 onwards, Multi-Factor Authentication (MFA) will be introduced to this site. This will add an extra step to the login process: a requirement to enter a One Time Passcode (OTP) upon login to minimise fraud and maintain security. See our summary page here for more details.

Open
Ref: 076-ATH-CFA034 Vacancy ID: 7317511

Data Scientist

Accepting applications until: 23-Jul-2025 23:59

Open

Accepting applications until: 23-Jul-2025 23:59

Location

1st Floor, Citygate
Gallowgate
Newcastle upon Tyne
NE1 4WH
Tyne and Wear

Contract type & working pattern

8 months (Fixed Term until 31st March 2025)
  • Flexible working
  • Home or remote working
37.5 hours per week

Salary

£53,755 - £60,504 per annum
Yearly

(NHS AfC: Band 8a)

Specialty

Data Science

The NHS Counter Fraud Authority (NHSCFA) is the national body responsible all for matters relating to the prevention, detection and investigation of economic crime across the NHS. Aligned to the DH Health Group Counter Fraud strategy, the NHSCFA acts as the principal lead for the NHS and wider health group in counter fraud intelligence work.

The NHSBSA is responsible for the processing of your application; a privacy notice is attached to advise you on how we will process your personal data.

Job overview

The NHS Counter Fraud Authority (NHSCFA) is the national body responsible for all matters relating to the prevention, detection and investigation of economic crime across the NHS. Further information about our work and annual plan for delivering this is available on our website.

The Data Scientist role requires expertise in machine learning, statistical analysis, anomaly detection, and strong communication and collaboration skills. Key responsibilities include developing innovative models, designing, applying, and optimising models in a dynamic environment. The role is critical in project planning, using data to drive business objectives, and defining project directions to achieve financial targets. With a deep understanding of data science, including machine learning, predictive modelling, and deep learning, the Data Scientist will tackle complex challenges and extract actionable insights from diverse datasets. They will lead model development and ensure solutions meet business and government standards. 

  The post holder will be required to have a NPPV2. 

Potential applicants can contact Susan Proctor on [email protected]  for an informal chat if you have any questions regarding the role.

We reserve the right to close this vacancy before the advertised closing date should we receive a significant number of applications.

Interviews will be held Online on 5th August 2025.

Advert

Collaboration across functions is essential to align data science initiatives with NHSCFA goals, ensuring accountability for innovative outcomes. Utilising the latest advanced methods, they will embed analytics into the organisation to enhance fraud detection within the NHS. 

Clear communication of statistical outputs and results to non-technical stakeholders is crucial, influencing decisions like criminal intervention, policy changes, or risk metrics based on data-driven insights. The role demands adherence to government data standards, ensuring data transparency, integrity, and compliance throughout the portfolio.

Prepare data for model development and selection using techniques such as, sampling, feature engineering and normalisation etc.

Leverage advanced AI and machine learning techniques, including deep learning, to improve fraud detection and prevention models while adhering to privacy regulations.

Working for our organisation

We have offices based in Coventry, Newcastle and London and offer flexible, hybrid, office and home-based working. The NHSCFA values and respects the diversity of its employees and aims to recruit a workforce which reflects our diverse communities. We welcome applications irrespective of people's age, disability, gender, race or ethnicity, religion or belief, sexual orientation, or other personal circumstances. We have policies and procedures in place to ensure that all applicants are treated fairly and consistently at every stage of the recruitment process, including an invitation to the first stage of the selection process and consideration of reasonable adjustments for people who have a disability. If you are applying to undertake this role on a secondment basis you should have agreement to being released from your current role in principle, prior to submitting an application form. When you apply for this role, you will be redirected to our recruitment system TRAC. The NHSCFA does not hold a sponsor licence in respect of skilled worker visas and so is unable to employ candidates requiring sponsorship.

Detailed job description and main responsibilities

·      

Create, deploy, and refine cutting-edge AI/Machine Learning algorithms and suitable methodologies to detect and anticipate evolving fraud patterns and trends.

·        Design innovative solutions to solve business problems in the identification of fraud and wider NHS to protect NHS money and resources from irregular activity.

 

Build highly accurate practical Machine Learning models, by developing supervised, unsupervised, and semi supervised models etc, creating end-to-end data pipelines and deploying outputs within the NHSCFA environment ready for action. 

Provide a deep understanding of the theoretical foundations behind classical and recent machine learning models and algorithms, such as generalised linear models, random forests, SVM, ensemble methods, and deep neural networks etc including assessment and justification of approaches and metrics and how each is used in a practical environment to detect anomalies/fraud within the NHS including providing verbal and written explanation of the results and key metrics. 

 

Minimise false positives while ensuring predication or classification accuracy is paramount.

 

Deploy the models in the operational environment and maintain/troubleshoot any production issues that arise.

 

Please see full job description and person specification.

 

Applicant requirements

The postholder will have access to vulnerable people in the course of their normal duties and as such this post is subject to the Rehabilitation of Offenders Act 1974 (Exceptions) Order 1975 (Amendment) (England and Wales) Order 2020 and as such it will be necessary for a submission for Disclosure to be made to the Disclosure and Barring Service to check for any previous criminal convictions.

Person specification

Knowledge and Experience

Essential criteria
  • Practical application experience in managing data science projects, from project design, method selection, control, optimisation, and implementation within the workplace. Including guidance, documentation, and leadership.
  • Proven experience of line managing a team of analyst as part of a data science project.
  • Knowledge and practical experience in designing algorithms including selection, using statistical and problem centric methods to design actionable outcome across a variety of data types.
  • Proven practical experience and expertise in AI/machine learning methods using data including the implementation of statistical modelling and methods into a live production environment.
  • Experience and strong proficiency in programming languages for data science, e.g., SQL, R and Python alongside the ability to use tools and packages such as Alteryx, Jupyter notebook, R Markdown, TensorFlow, Keras, Pytorch etc.
  • Practical expertise in producing reproducible code and pipelines including documentation, governance and assurance frameworks, automation and code review using tools such as Git.
  • Skilled in data visualisation, with expertise in employing best practices and a proven track record of effectively communicating statistical findings to stakeholders.
  • Strong analytical and problem-solving skills, with the ability to analyse large and complex datasets, extract meaningful insight and actionable outcome to help inform business outcome.
  • Practical experience in model development and production and the alignment with model governance, business, best practice, and regulatory standards.
Desirable criteria
  • Expertise and proven experience of fraud/anomaly detection.
  • Extensive understanding of the NHS data landscape.
  • Accredited Counter Fraud Specialist or member of Government Counter fraud Profession

Specialist Knowledge/Skills

Essential criteria
  • Proven experience in advanced data science techniques and statistical modelling methodologies within large and complex datasets.
  • Practical and proven expertise of machine learning algorithms, including supervised, unsupervised, and semi supervised techniques used to build and deploy models.
  • Significant expertise of techniques used to prepare data for model selection, such as sampling, normalisation, imputation including theoretical knowledge.
  • Proven experience in operating within a big data environment, encompassing the management of substantial data volumes sourced from diverse origins, including data handling, pre-processing, scalability, storage optimisation, and the application of efficient processing methodologies.
  • Proven experience in generating, analysing, and interpreting data within professional settings, demonstrating a deep understanding of data exploration, statistical theory and understanding of the results produced, statistical inference, and predictive modelling principles.
  • Practical experience in critically assessing and explaining computational and mathematical outcomes, including model selection, evaluation. Demonstrating transparency and assurance processes are fully documented and justified.
  • Practical experience in critically evaluating and explaining computational and mathematical results, encompassing model selection and evaluation. Demonstrating transparency and assurance processes are fully documented and justified.
  • Practical expertise and expertise in a professional capacity with GDPR and privacy laws which significantly impact data science practices.
Desirable criteria
  • Knowledge of generative AI models involving NLP across both open and closed large language models.
  • Domain knowledge of key NHSCFA thematic areas and corresponding datasets across the NHS, wider public sector and beyond.
  • Practical expertise of machine learning algorithms used to detect fraudulent activity.

Qualifications

Essential criteria
  • Degree, in numerate subject or equivalent experience/learning developed in a similar role (e.g., Mathematical, Data Science, Computer Science, Physics, or related discipline). For the purposes of this job description equivalent experience would be management and technical experience in a similar sized and complex organisation, successfully providing the technical ability concerning data science alongside the necessary drive, leadership, and direction.
  • Have worked in a statistical/data science field and are able to demonstrate continuous professional development.
Desirable criteria
  • Master’s degree in numerate subject or equivalent experience/learning developed in a similar role (e.g., Mathematical, Data Science, Computer Science, Physics, or related discipline).

Communication Skills

Essential criteria
  • Advanced written and verbal communication skills, including the presentation of complex information, writing, presenting, and other documentation to both internal and external stakeholders.
  • Effectively communicate and articulate findings to stakeholders at all management levels, addressing challenges to results with, justification, clarity, and precision.
  • Must be able to provide and receive highly complex, sensitive, or contentious information, negotiate with senior stakeholders on difficult and controversial issues, and present complex and sensitive information to influential groups.
  • Can lead, manage, and motivate a team, including the devising and explanation of complex methodologies and methods.
Desirable criteria
  • Politically astute with knowledge of national and regional decision making and influencing bodies.
  • Provided expert guidance on data science methodologies and results within the NHS.

Documents

Further details / informal visits contact

Name
Susan Proctor
Job title
Data Scientist SME Manager
Email address
[email protected]

Start your application

You must sign in to a Trac account before you can apply for this job.

Sign in

By signing in you are acknowledging our privacy notice.

Create an account

Create your account and apply for your new job!