Data Analyst - Fraud Risk Management
- Wilmington, DE, USA Wilmington DE US
- Contract, Full time
- Barclays - US
- 25 May 18 2018-05-25
Overall purpose of role To support the Fraud Transaction Cycle in meeting its objectives * Provide fraud strategy input and intelligence for initiatives under Fraud Transaction Cycle * Integrate and maximize value from fraud solutions originating from Fraud Transaction Cycle
- Perform analysis of current and historic data (e.g. applications, write off data) in the support of Fraud TC initiatives
- Track and monitor capabilities enabled by fraud TC and provide intelligence to support those capabilities
- Identification of data driven fraud trends and development of solutions to address the trend
- Provide support, including analysis, to various Strategic Fraud initiatives outlined by the business as and when necessary
Stakeholder Management and Leadership
- Organizational awareness - Ability to see the 'whole picture' and recognize the impact and opportunities of activities across the organization.
- Team Player - Ability to work with and in cross-functional and virtual teams.
- Communication - Effectively and concisely communicate key issues and ideas through correspondences and verbally without supervision. Interface with stakeholders effectively.
Decision-making and Problem Solving
- Analytical ability - Must have a clear understanding and experience in performing data analysis using a standard statistical package such as SAS/SQL
- Ability to solve advanced problems and deal with a variety of options in complex situations
- Innovation - Create innovative solutions to satisfy business requirements with analysis where needed
Risk and Control Objective
Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Wide Risk Management Framework and internal Barclays Policies and Policy Standards.
- 2+ years of strategy/analytics experience required, preferably in risk management/modelling function.
- 2+ years of strong analytical skills, technical skills in SAS/SQL and statistical skills with proven ability to process vast amounts of data into meaningful information.
- Bachelor's degree in a quantitative discipline like Statistics, Mathematics, Operations Research etc.
- Experience in Card fraud detection strongly preferred, but not required.
- Knowledge on Data Science (Hadoop/Big Data/Machine Learning) is preferred, but not a strict requirement
- Master's degree strongly preferred