Fraud Technical Data Analyst

Join us as a Fraud Technical Data Analyst where you'll play a critical role in designing and delivering data-driven solutions that support fraud detection, prevention, and reporting. This technical role blends evaluative depth with strategic insight, enabling collaboration across fraud, data technology, and business teams to protect customers and the organisation from financial crime.

To be successful as a Fraud Technical Data Analyst, you should have experience with:

• Capturing and translating business needs into scalable technical solutions with stakeholders.
• Using SAS and SQL for data exploration, reporting, and technical processing, working with large datasets
• Experience with different data management techniques including ETL, CDC, and data warehousing tooling

Some Other Highly Valued Skills May Include

• Experience in fraud prevention, detection or investigation within the financial services sector.
• Certifications in SAS, AWS, or Python, and knowledge of ETL and data warehousing.
• Data visualisation with Tableau or Power BI, and fraud experience in financial services.
• Working across time zones and applying knowledge of Spark, Databricks, and data compliance.

You may be assessed on the key critical skills relevant for success in this 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 will be based in Northampton.

Purpose of the role
To implement data quality process and procedures, ensuring that data is reliable and trustworthy, then extract actionable insights from it to help the organisation improve its operation, and optimise resources.

Accountabilities

• Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification.
• Execution of data cleansing and transformation tasks to prepare data for analysis.
• Designing and building data pipelines to automate data movement and processing.
• Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems.
• Documentation of data quality findings and recommendations for improvement.

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, 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.