AVP - Fraud Analytics

Barclays•Wilmington, DE

2d•Onsite

About The Position

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. Embark on a transformative journey as an AVP - Fraud Analytics. At Barclays, our vision is clear – to redefine the future of banking and help craft innovative solutions. You will join a dynamic data analytics team supporting the Fraud function within the Cards business at Barclays. As part of a global analytics group, you will contribute to managing fraud rules and models that enhance the performance of Fraud strategies and policies. Become a key member of a team that delivers meaningful impact to the business.

Requirements

Programming experience in SQL/SAS/Unix/Oracle programming or equivalent with adjacent tools such as Python
Experience in performing data and statistical analysis for fraud strategy development & management or similar risk management function
Ability to deliver data‑driven insights that enhance the effectiveness of fraud risk systems, toolkits, and related data processes—directly supporting the early detection of fraud and helping minimize fraud losses
Experience working closely with technical, strategy, and business teams to develop and prioritize key projects and resource plans that optimize existing capabilities

Nice To Haves

Experience with data visualization tools, such as Tableau
AI, machine-learning, and Databrick/Snowflake tool usage experience is a plus
Partnership with modelling teams to introduce new effective models into the system
Experience with governance and control teams to ensure proper documentation, risk ratings, and controls in place for all rule and model executions

Responsibilities

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.
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
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.
Influence or convince stakeholders to achieve outcomes.