Data Scientist

Job 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.

Knowledge and Experience

Essential

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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.

Disclosure and Barring Service Check

This post is subject to the Rehabilitation of Offenders Act (Exceptions Order) 1975 and as such it will be necessary for a submission for Disclosure to be made to the Disclosure and Barring Service (formerly known as CRB) to check for any previous criminal convictions.

Certificate of Sponsorship

Applications from job seekers who require current Skilled worker sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas and Immigration website (Opens in a new tab).

From 6 April 2017, skilled worker applicants, applying for entry clearance into the UK, have had to present a criminal record certificate from each country they have resided continuously or cumulatively for 12 months or more in the past 10 years. Adult dependants (over 18 years old) are also subject to this requirement. Guidance can be found here Criminal records checks for overseas applicants (Opens in a new tab).