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Join our Financial Crime Detection team as Senior Analyst Transaction Monitoring Detection & Optimization and elevate the precision and performance of Barclays’ global transaction monitoring. This AVP position plays a significant role in helping to strengthen the way we identify and respond to financial crime risk. In this role, you’ll take an active hand in enhancing our TM solutions across Barclays UK and Barclays International, diving deep into model performance, evaluating system behaviour, and collaborating with partners across Model Validation, Technology, and Financial Crime. You will support the development and optimization of automated detection capabilities, work closely with stakeholders to understand emerging priorities, and identify opportunities to elevate the effectiveness and precision of our monitoring framework. This is your chance to shape critical detection tools and contribute to a more resilient, data‑driven control environment.
Job Responsibility:
Acquisition and collection of data from various sources, including internal databases, external datasets, and real-time feeds
Performing data cleaning and pre-processing tasks to ensure data quality and suitability for model development
Design and implementation of data management strategies for model maintenance and future development
Designing, development, and implementation of statistical and machine learning models for various applications, including credit risk assessment, fraud detection, customer segmentation, and marketing optimisation
Monitoring model performance in real-time and identify any potential issues or biases
Leading training, mentoring, and knowledge-sharing sessions to uplift ML capability across the organisation
Evaluating and piloting emerging technologies, tools, and frameworks to ensure the organisation remains at the forefront of AI innovation
Requirements:
Transaction Monitoring Model & Controls experience
Critical thinking and Analytical mindset
The ability to solve problems logically and/or creatively, demonstrating professional judgment, quality control, and adherence to high standards
Nice to have:
In-depth understanding of Financial Institution data (e.g. Customer/Account, Transactional, Payment), systems and flows
Familiarity with latest TM Machine Learning model techniques and traditional TM systems (Actimize, Mantas, Quantexa)
Understanding of statistical concepts such as descriptive statistics, sampling, classification, and its application towards setting up and optimizing TM systems