Job Description

Purpose of the role

To design, develop, implement, and maintain various statistical, mathematical and machine learning models to support decision-making by analysis and solving complex problems. 

Accountabilities

• 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. 

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Join us at Barclays as a Financial Crime Data Analyst. Be part of our transaction monitoring team and leverage data analytics expertise within the financial crime space.

To be successful as a Financial Crime Data Analyst, you should have experience with:

• Hands on experience in Python and SQL
• Strong analytical skills, rule development skills, with understanding of ML
• SME Knowledge in transaction monitoring/money laundering financial crime analytics tasks

Some other highly valued skills may include:

• Knowledge of risk coverage related to money laundering and terrorist financing.
• Familiarity with the current regulatory landscape within financial crime compliance.
• Background in mathematics or statistics, including areas such as probability, machine learning, and AI.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role is based in Glasgow.