Analytics Assurance - AVP

Barclays Services LLC seeks Analytics Assurance – AVP in Wilmington, DE (multiple positions available): Examine data repositories and generate periodic reports to assist with resolution of consumer and commercial card and loan bank wide issues for the Customer Remediation Team ("CRT") within Barclays Customer Delivery business. Create complex queries utilizing SAS, Python, and Tableau to extract data from multiple data sources. Utilize SAS to query bank databases to identify accounts impacted by opened incidents. Utilize SQL and Oracle SQL programming to extract, load, and transform customer specific data. Utilize SAS analytics and SAS Grid to design and create datasets from various sources including MS excel, MS Access, flat files, and Oracle files. Utilize UNIX scripts for automating processes and integration within existing operational framework. Utilize TSYS mainframe through Visual basic and SAS Scripts as per test scenarios to condition test data and validate test results. Utilize PL/SQL and SQL loader calling Unix Scripts to download and manipulate files. Responsible for developing UNIX Shell scripts for Batch processing of data files to update accounts. Identify accounts as defined by business requirements. Ensure the validation of files and assist in making changes as needed based on requirements and the creation of batch update files. Compile and validate lists and apply remediation treatment on impacted accounts. May telecommute pursuant to company policies (hybrid role). This position is eligible for incentives pursuant to Barclays Employee Referral Program. Purpose of the role: To enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports. Accountabilities: Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement. Designing and building data pipelines to automate data movement and processing. Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI. Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements. Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs.