1 to 25 of 95 Permanent Fraud Detection Jobs in the UK

claims solutions we support end-to-end claims handling with analytics and automation tools that streamline workflow, improve claims management and support better customer experiences. We also provide a fraud detection service across multiple perils and lines of business. Using intel processing, real-time fraud analysis and image forensics we help detect fraud at every stage More ❯

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 … 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 ❯

wrangling to compose meaningful feature and clean sets, and modelling using Machine Learning. You'll develop and deploy machine learning models that power real-world decisions - from underwriting to fraud detection to optimise customer conversion. This is an end-to-end role: data wrangling, model development, evaluation, and performance monitoring. As a Data Scientist, you'll play a More ❯

business challenges, design and implement data-driven solutions, and provide actionable insights that drive business value. Your ability to address challenges specific to financial services, such as risk modeling, fraud detection, and regulatory compliance, will be a critical asset. #LI-DNI Responsibilities Support financial services clients with the definition and implementation of their AI strategy, focusing on areas … an emphasis on regulatory compliance (e.g., Basel III, GDPR) and ethical AI principles Ideate, design and implement AI-enabled solutions for financial services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments … MiFID II or the EU AI regulatory framework Deep understanding of LLMs and their application in areas like financial document analysis, customer service chatbots or regulatory reporting Expertise in fraud detection techniques, anomaly detection and compliance analytics Strong understanding of ML Ops principles and experience in deploying and managing AI/ML models in financial systems Proficiency More ❯

business challenges, design and implement data-driven solutions, and provide actionable insights that drive business value. Your ability to address challenges specific to financial services, such as risk modeling, fraud detection, and regulatory compliance, will be a critical asset. #LI-DNI Responsibilities Support financial services clients with the definition and implementation of their AI strategy, focusing on areas … an emphasis on regulatory compliance (e.g., Basel III, GDPR) and ethical AI principles Ideate, design and implement AI-enabled solutions for financial services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments … MiFID II or the EU AI regulatory framework Deep understanding of LLMs and their application in areas like financial document analysis, customer service chatbots or regulatory reporting Expertise in fraud detection techniques, anomaly detection and compliance analytics Strong understanding of ML Ops principles and experience in deploying and managing AI/ML models in financial systems Proficiency More ❯

excellent customer outcomes. This role focuses on analysing customer data, evaluating credit risk policies, forecasting and monitoring portfolio performance to identify areas for improvement. You will also contribute to fraud detection and prevention strategies, leveraging your skills to protect both the business and our customers. Working closely with the Credit Risk Manager and collaborating with teams across product … strategies. Support the development and implementation of credit risk models and decision systems, ensuring they align with business goals. Take ownership of key metrics related to credit risk and fraud, identifying trends and recommending improvements to strategies and policies. Drive fraud analytics by identifying and analysing patterns related to first-, second-, and third-party fraud, working with … the Fraud team as needed. Influence senior stakeholders through the presentation of analysis and recommendations in order to drive impactful change. Collaborate with the data engineering and product teams to enhance data quality and ensure efficient integration of credit risk tools and systems. Support in testing and validating new credit risk tools, processes, and decision-making frameworks. Stay updated More ❯

DAC Beachcroft. The team provides analytics products to both internal and external clients in a wide range of areas, including performance and operational analysis, market trends, predictive modelling and fraud detection. This is an area of rapid development, with the team leading the way in making a truly intelligence led organisation. This role can be done on a remote More ❯

DAC Beachcroft. The team provides analytics products to both internal and external clients in a wide range of areas, including performance and operational analysis, market trends, predictive modelling and fraud detection. This is an area of rapid development, with the team leading the way in making a truly intelligence led organisation. This role can be done on a remote More ❯

DAC Beachcroft. The team provides analytics products to both internal and external clients in a wide range of areas, including performance and operational analysis, market trends, predictive modelling and fraud detection. This is an area of rapid development, with the team leading the way in making a truly intelligence led organisation. This role can be done on a remote More ❯

DAC Beachcroft. The team provides analytics products to both internal and external clients in a wide range of areas, including performance and operational analysis, market trends, predictive modelling and fraud detection. This is an area of rapid development, with the team leading the way in making a truly intelligence led organisation. This role can be done on a remote 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 … workflows and help embed models into production systems Analyse transaction and behavioural data to identify trends, anomalies, and fraud patterns Requirements Industry experience in data science or machine learning models, ideally in fraud, financial crime, or a related domain Experience working with large-scale, high-dimensional, and heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding 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 ❯

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 ❯

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 ❯

handle routine inquiries, provide 24/7 support, and reduce wait times. Sentiment Analysis: Use AI to analyze customer feedback and sentiment from various channels to improve services. 2. Fraud Detection and Prevention Real-Time Monitoring: Implement AI algorithms to detect and flag unusual transactions in real-time. Predictive Analytics: Use machine learning models to predict potential fraud More ❯

wrangling to compose meaningful feature and clean sets, and modelling using Machine Learning. You'll develop and deploy machine learning models that power real-world decisions - from underwriting to fraud detection to optimise customer conversion. This is an end-to-end role: data wrangling, model development, evaluation, and performance monitoring. As a Data Scientist, you'll play a More ❯

predictive maintenance pipelines for government departments. Build Solutions That Scale: Your analytics engineering will power data products used by millions of customers, from recommendation engines for major retailers to fraud detection systems for financial institutions. Shape Technical Standards: As a growing consultancy, you'll help define our analytics engineering practices, tooling choices, and data architecture patterns that will More ❯

partners in digital banking and financial services. With a strong focus on customer experience, innovation, and security, we are committed to maintaining the trust of our users through robust fraud prevention and detection frameworks. Role Overview As a Fraud Manager, you will lead a team responsible for identifying, investigating, and mitigating fraud risks across our digital … banking products and services. You will play a key role in shaping fraud strategy, implementing proactive controls, and enhancing our fraud monitoring capabilities. Key Responsibilities Lead the fraud detection and prevention team, ensuring effective monitoring and investigation of suspicious activities. Develop and implement fraud risk management strategies and policies aligned with regulatory requirements and industry … Utilize data analytics, rules engines, and machine learning models to detect unusual patterns and prevent fraudulent transactions. Collaborate with Product, Engineering, Customer Service, Compliance, and Legal teams to enhance fraud controls across customer journeys. Manage fraud case investigations, reporting, and escalations, ensuring timely resolution and customer impact mitigation. Monitor KPIs and generate regular fraud performance reports for More ❯

big ambitions, we've achieved double unicorn status and serve over 5 million customers. We have exciting projects ahead and significant growth plans. The role. We are seeking a Fraud Manager responsible for developing and implementing strategies to prevent and detect fraud. This role involves collaborating with teams such as Credit Risk and Engineering, monitoring fraud trends, leading … analysts, and coordinating with external partners to ensure effective case resolution. The Fraud Manager will also report on fraud metrics to leadership and utilize data analytics to enhance detection methods, protecting both the company and its customers. Day-to-day responsibilities. Develop, execute, and refine Zilch's fraud management framework and strategy. Monitor emerging fraud trends and threats, working with Credit Risk, Product, and Engineering teams to implement proactive measures to reduce fraud losses. Stay informed about new fraud trends and mitigation strategies in the market. Create standardized policies, procedures, and controls for fraud detection, prevention, and reporting. Assess and improve fraud workflows for seamless case handling and explore 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, About the team: You will be part of a team … who use global data from the largest real-time fraud detection platform to craft solutions for our enterprise customers. About the role: Your experience with data analysis, statistical modelling, and machine learning will lead to immediate real-world impact in the form of lower customer friction, reduced fraud losses and as a result, increased customer profitability. You … craft a story through data, delivering industry-leading presentations for external and executive audiences Building an extensive knowledge of cybercrime - account takeover, scams, social engineering, Card Not Present (CNP) fraud, money laundering and mule fraud etc Employing your multi-tasking and prioritisation skills to excel in a fast-paced environment with frequently changing priorities Requirements: Experience in a More ❯

uncover trends and patterns that inform our business strategy. Your insights will play a key role in shaping decisions across various business areas, including marketing, sales, claims, customer retention, fraud detection, and customer servicing. As a Data Scientist, you'll collaborate closely with cross-functional teams, including product management and engineering, to identify an integrate your findings into … trends in data, providing insights to inform business strategy and decision-making. Develop predictive models to support decisions across multiple business areas, including marketing, sales, claims, retention, customer behavior, fraud detection, and customer servicing. Deploy machine learning models into production using AWS services, including SageMaker, S3, Feature Store, ensuring scalable, reliable, and monitored solutions that directly support key More ❯

the full lifecycle of model development —from data wrangling and feature engineering to building and deploying ML models in production. Your work will directly power business decisions across underwriting, fraud detection, and customer conversion . This is a hands-on, end-to-end role where your skills in predictive modelling will make a real-world impact. You’ll More ❯

the full lifecycle of model development —from data wrangling and feature engineering to building and deploying ML models in production. Your work will directly power business decisions across underwriting, fraud detection, and customer conversion . This is a hands-on, end-to-end role where your skills in predictive modelling will make a real-world impact. You’ll More ❯

optimization, and much more. FICO makes a real difference in the way businesses operate worldwide: • Credit Scoring - FICO Scores are used by 90 of the top 100 US lenders. • Fraud Detection and Security - 4 billion payment cards globally are protected by FICO fraud systems. • Lending - 3/4 of US mortgages are approved using the FICO Score. More ❯

mission to help businesses improve decision-making using AI, machine learning, and optimization. FICO makes a difference worldwide: Credit Scoring - Used by 90 of the top 100 US lenders. Fraud Detection - Protects 4 billion payment cards globally. Lending - Used in 75% of US mortgages. Join us to be part of a diverse, inclusive environment that fosters collaboration and More ❯