Fraud Modelling Analyst

at Barclays Bank Delaware in Wilmington, Delaware, United States

Job Description

Barclays Services Corp. seeks a Fraud Modelling Analyst for its Wilmington, DE 19801 location.

Duties: Develop and maintain machine learning models used for fraud detection and business financial planning. Develop best in class decision tools using Anaconda Server, H2O, Hadoop, Hive, Impala and Spark. Formulate and apply statistical modelling, and use statistical and quantitative analysis and techniques to develop models used to mitigate loss of credit card business. Work with team members in the Global Fraud Management and Technology teams to understand objectives, issues, and develop solutions contributing to model related decisions. Plan and deliver fraud detection models for portfolios, meeting agreed deadlines and ensuring implementation of models in production systems. Deliver insights and recommendations to improve business strategy and process. Perform annual reviews, performance monitoring reviews, retrains, and remediation activity on models as required. Ensure all deliveries conform to Model Risk Governance Framework and regulatory requirements, and produce robust, clear documentation. Keep abreast of machine learning and fraud detection industry developments, conducting R&D to incorporate best in class modelling methodologies and disseminating learnings within the team. Identify and evaluate the incremental value of additional information sources.

Requirements: Requires Master’s degree or foreign equivalent in Statistics, Mathematics, or closely related quantitative field plus two (2) years of experience in position offered or in a related Statistical Analyst, Modeling Analyst, or Model Developer role for a global financial services firm. Full term (2 years) of experience must include: Analyzing data, developing and implementing quantitative models using SAS, Python and H2O; Utilizing statistical analysis to manipulate and prepare/process data for model development; Using machine learning techniques to develop fraud detection models; Using big data skillsets including Anaconda server, H2O, Hadoop, Spark, Hive, and Impala to create features and develop models from datasets in Hadoop Cluster. Must have knowledge of: mathematical and theoretical modeling, historical back-testing, statistical analysis with statistical inference, data clustering, regression and classification, and machine learning tools including Oracle.

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Job Posting: 841842

Posted On: Sep 07, 2021

Updated On: Oct 20, 2021