Financial Crime Analyst

Barclays; Northampton; Hybrid; GBP 75,000 - 110,000; Full time

Job summary

Barclays in Northampton is seeking an experienced Financial Crime Analytics Assistant Vice President to develop and enhance analytics capabilities that identify, prevent and disrupt money mule activity across the bank’s customer base and payment networks. The role requires advanced data analysis skills and strong programming capabilities.

You will work on designing statistical and machine learning models, building robust data pipelines, and communicating complex analytical insights to both

Qualifications

• Advanced experience analysing large, complex datasets to identify patterns, trends and risks.
• Experience in Fraud/Financial Crime/AML or risk analytics with an analytical focus.
• Proficiency in SQL and Python and/or SAS for data analysis and modelling.
• Degree in a STEM discipline or equivalent quantitative analysis experience.

Responsibilities

• Identify, collect and extract data from internal and external sources.
• Clean, wrangle and transform data for quality analysis.
• Develop and maintain data pipelines for automated acquisition and processing.
• Design and implement statistical and machine learning models to analyse patterns and relationships.
• Develop predictive models to forecast outcomes and identify risks and opportunities.
• Collaborate with stakeholders to add value from data through Data Science.

Skills

Data analysis

Fraud analytics

SQL

Python/SAS

Education

STEM degree

Tools

SQL

Python

SAS

Job description

Join us at Barclays! We are seeking an experienced Financial Crime Analytics Assistant Vice President. This role is responsible for developing and enhancing analytics capabilities that identify, prevent and disrupt money mule activity across the bank’s customer base and payment networks.

To be successful as a Financial Crime Analyst, you must have the following essential skills:

• Advanced experience analysing large, complex datasets to identify patterns, trends and emerging financial crime risks.
• Proven experience within Fraud, Financial Crime, Anti-Money Laundering (AML), Credit Risk or other risk analytics functions, with an analytical focus.
• Advanced proficiency in SQL and Python and/or SAS for data extraction, transformation, modelling and analytical insight generation.
• Degree in a STEM discipline (e.g. Mathematics, Statistics, Computer Science, Engineering) or equivalent quantitative analytical experience.

Some other highly valued skills may include:

• Banking experience, with an understanding of customer account and transaction data.
• Understanding of controls, governance, model risk management, and regulatory compliance within a highly regulated environment.
• Ability to communicate complex analytical findings clearly to both technical and non-technical stakeholders.

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 Northampton.

#LI-Hybrid

Purpose of the role

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.

Accountabilities

• Identification, collection, extraction of data from various sources, including internal and external sources.
• Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
• Development and maintenance of efficient data pipelines for automated data acquisition and processing.
• Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.

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.