VP Transaction Monitoring Data Analyst

Barclays • New York, NY

3d • $160,000 - $210,000 • Onsite

About The Position

Join our Financial Crime Analytics team as VP Transaction Monitoring Data Analyst and play a pivotal role in shaping the end-to-end lifecycle of TM detection solutions across Barclays UK and Barclays International. This position partners closely with other Financial Crime Detection specialists, Technology, Operations, and business stakeholders to align detection analytics capabilities with evolving priorities and emerging risks. You will provide experienced oversight of global TM models, engage with validation and data teams to address highly detailed model related considerations, and support the advancement of automated detection capabilities that enhance precision, efficiency, and overall control effectiveness. This is a high impact opportunity to influence critical monitoring frameworks and strengthen the bank’s intelligence focused approach to financial crime risk management.

Requirements

• Experience in utilising analytical tools for data exploration, analysis and visualisation, including coding ability and experience on Python and SQL.
• In-depth understanding of Financial Institution data (e.g. Customer/Account, Transactional, Payment), systems and flows, data lineage, data mapping as well as data enrichment.
• Understanding of Financial Crime, AML and Transaction Monitoring/detection and the systems/processes, including an understanding of AML and terrorist financing trends and typologies.
• Relevant qualifications in data analytics and technical field, with familiarity on databases and data transformation.

Nice To Haves

• Experience of a Regulated Business Environment with exposure to governance, control, and risk management.
• Knowledge of the Global Financial Crime regulatory framework.

Responsibilities

• 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.
• Contribute or set strategy, drive requirements and make recommendations for change.
• Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures.
• If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes.
• Lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.
• Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
• Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
• Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives.
• In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
• Adopt and include the outcomes of extensive research in problem solving processes.
• Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.
• Provide experienced oversight of global TM models.
• Engage with validation and data teams to address highly detailed model related considerations.
• Support the advancement of automated detection capabilities that enhance precision, efficiency, and overall control effectiveness.

Benefits

• The minimum and maximum salary/rate information above includes only base salary or base hourly rate. It does not include any other type of compensation or benefits that may be available.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed