Job summary
The NHSCFA is the national body responsible for all matters relating to the prevention, detection and investigation of economic crime across the NHS. Further information can be found on our website.
We are embarking on a piece of work to monitor data to identify and respond to patterns indicative of potential fraud. This will support our current work that reduces the likelihood of fraud occurring. We will bring in data science capabilities to be deployed in counter fraud activity and work closely with partners across health and government to further maximise the preventative impact of proactive counter fraud analysis. We will combine this with our range of counter fraud and domain expertise to maximise our impact using your knowledge, experience, and passion for your chosen field. At the core will be the development and use of appropriate analytical techniques that include advanced analytics and machine leaning to tackle some of the highest areas of fraud risk to the NHS and ultimately protect public funds for patient care.
The role of the Senior Analytical Specialist is pivotal within the program, requiring a deep understanding of analytical techniques and methods used to examine and explore data, additional expertise in anomaly detection is essential. You will be expected to apply advanced techniques including using machine learning and understanding how to select the correct approach as well as interpret and explain results to others.
Interviews will be held
Main duties of the job
The successful candidate will work alongside other data science and response professionals, providing assistance across a wide range of information areas. This includes information/data collation, analysis, interpretation, data structure, and evaluation. They will collaborate with various organisations and domain experts to understand systems and data collection processes, resulting in the production of actionable insights for the program of work to take forward.
They will understand current and emerging technologies, utilising statistics, coding and analytical tools like SQL, R, Python, and Alteryx, ensuring all processes adhere to governance and regulatory standards.
The post holder will be required to have a NPPV2.
About us
We have offices based in Coventry, Newcastle and London and offer flexible, hybrid, office and home-based working. In addition to the advertised salary working in the London area will attract High-Cost Area Supplement where appropriate. 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.
We reserve the right to close this vacancy before the advertised closing date should we receive a significant number of applications.
Job description
Job responsibilities
Use advanced analytical methods to perform detailed data analysis using a variety of statistical techniques to identify trends and patterns.
Apply statistical, and operational research techniques to effectively model and analyse a variety of data sources, and make recommendations based on findings to support preventative, operational and strategic business decisions.
Use advanced statistical techniques to identify and analyse anomalies within data sets which may be indicative of fraud.
Design innovative solutions to solve business problems in the identification of fraud and wider NHS to protect NHS money and resources from irregular activity.
Examine suspected anomaly causes as they occur, together with the team, domain, and fraud experts, by translating complex information/intelligence into detectable patterns in data and selecting the right methods/models to approach the explicit issue.Please see full Job Description and Person Specification.
Person Specification
Knowledge and Experience
Essential
Practical application expertise of managing data projects involving statistical methods and machine learning using structured approach frameworks and project methodologies. 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. Experience of producing reproducible dynamic processes and code. Practical application in using Alteryx, R, and Python to produce accurate data analysis, encompassing all ETL steps including data extraction, transformation, and loading, ensuring accuracy and reliability. Demonstrable experience in managing deadlines and prioritising workloads, and maintaining high analytical standards. Practical expertise of using data to influence strategic direction. Experience and understanding of cloud computing and efficient processing techniques in a big data environment. Practical experience in working with teams, and domain experts to identify and analyse anomalies, translating information into detectable patterns.
Desirable
Experience understanding of the NHS data landscape. Experience of using SQL.
Specialist Knowledge
Essential
In depth specialist knowledge of information analysis and the use of data across the NHS. Practical expertise of analysis methods including advance statistical techniques used to extract meaningful and accurate actionable insight. Skilled in data visualisation, with expertise in employing best practices and a proven track record of effectively communicating statistical findings to stakeholders. Practical experience in data management, including examining external systems and data structures, and understanding the impact of policies and regulations on data sources. Knowledge of Data Protection Act and confidentiality and information governance issues.
Desirable
Understanding of the techniques used to identify fraudulent behaviour within datasets.
Qualifications
Essential
Degree, in numerate subject or equivalent experience/learning developed in a similar role (, Mathematical, Data Science, Computer Science, 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 analysis.
Desirable
Post-graduate or equivalent in related field or equivalent relevant experience. Accredited Counter Fraud Specialist or member of the Government Counter Fraud Profession.
Communication Skills
Essential
Excellent communication and interpersonal skills, with the ability to present and interrupt complex systems, data structures and results to technical and non-technical experts' using methods such as dynamic tools, written and visual. Must be able to handle highly complex, sensitive, or contentious information, negotiate challenging issues with senior stakeholders, and effectively present complex and sensitive information to influential groups. Effectively communicate and articulate findings to stakeholders at all management levels, addressing challenges to results with, justification, clarity, and precision. Strong negotiation, analytical and conflict resolution skills.
Desirable
Politically astute with knowledge of national and regional decision making and influencing bodies.