6 of 6 Fraud Detection Jobs in the North of England

Job summary 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 … 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 … 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. About us We have offices based in Coventry, Newcastle and London and offer flexible, hybrid, office and home-based More ❯

your own projects, drive modelling initiatives, and take ideas from concept to production You'll be encouraged to propose new approaches and explore creative ways to detect and prevent fraud We debate and critique our ideas in a healthy, supportive team You'll have the chance to shape both models and how we think about fraud detection … that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning … warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to quantify the level of fairness and bias machine learning models Enthusiasm for improving fraud detection systems and a proactive, problem-solving mindset Interview process Interviewing is a two way process and we want you to have the time and opportunity to get More ❯

Our client is looking for a Senior Data Analyst to join their Financial Crime, Claims and Operations Oversight team. This is your opportunity to use data for good — detecting fraud, strengthening controls, and influencing how they protect their customers and their business. Responsibilities; As a Senior Fraud Data Analyst, you’ll play a vital role in fraud prevention, governance, and operational risk oversight. You’ll: Lead data analysis and machine learning initiatives to detect suspicious activity and organised fraud Build predictive models and insight tools that enhance fraud detection, customer understanding, and business performance Ensure oversight and compliance across claims and operational processes, supporting fair customer outcomes Deliver high-impact reporting and dashboards More ❯

combines strong technical expertise with relationship management, and a deep understanding of customer operational challenges. Technical Skills/Experience Strong background in software configuration and system optimisation. Experience with fraud detection, risk management, security analytics or CCTV platforms. Proficiency in troubleshooting complex technical systems including the ability to read and interpret software logs. Ability to research and propose … preferred but not essential, practical experience and problem-solving skills are prioritized over specific degrees. Experience in enterprise-level application deployment. Background in retail loss prevention, security systems, or fraud detection preferred. Key Responsibilities Configure and deploy software tailored to customer needs. Optimise system performance and troubleshoot technical issues. Collaborate with clients to understand operational challenges and design More ❯

maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below, risk.lexisnexis.com About the Team The Customer Engagement team acts as … a centre of excellence for the LexisNexis® RiskNarrative® product, responsible for delivering Strategic Engagement Services to customers throughout their lifecycle. RiskNarrative brings powerful automation under total control, uniting fraud detection, financial crime prevention, compliance and risk management across the entire customer lifecycle for our customers. About the Role You will support the ongoing management and optimisation of existing … Able to react well to rapidly changing requirements with a positive attitude Able to meet deadlines while delivering an exceptional customer experience Having experience working in the financial crime & fraud sector is beneficial, however not essential We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are More ❯

and PSP licensing. Proven success leading large-scale B2B financial product initiatives. Technical fluency in API-first architecture, and ideally exposure to AI/ML tools for predictive finance, fraud detection, and reconciliation. Strong communicator and relationship-builder with the ability to influence at all levels. Desirable experience: Previous exposure to regulated sectors such as fintech or B2B More ❯