Business Analytics Lead Analyst

Master’s degree or foreign equivalent in IT and Management, Business Analytics, Data Analytics, Engineering (any) or related field
3 years of experience as a Fraud Analyst, Fraud Risk Analyst, Business Analytics Analyst or related position
Alternatively, a Bachelor’s degree in the stated fields and 5 years of specified progressive, post-baccalaureate experience
3 years of experience must include: Conducting data mining, data processing and modeling using SAS programming; Data Analytics tools and techniques to extract information from data; SQL; Database Management; Developing dynamic dashboards using Tableau data visualization tool; Analyzing fraud patterns using software packages SAS, R, Python Libraries; Teradata; Fraud analytics for the financial industry.

Conduct complex analysis to identify authentication and fraud detection gaps/issues at the strategy and portfolio levels and recommend path of action
Analyze fraud patterns using software packages SAS, R, Python Libraries
Develop dynamic dashboards using Tableau data visualization tool
Use SAS, SQL, Teradata, and Business Intelligence tools; leverage customer data to build risk segmentation and detection strategies
Derive trends and patterns via seemingly unconnected data sources
Leverage analytical tools and data science techniques to extract information from data
Analyze fraud patterns libraries in Python
Continuously optimize processes and look for new methods and opportunities to leverage fraud threat intelligence
Manage significant fraud events by helping coordinate information sharing across Global Consumer Bank Fraud prevention
Partner with cross-functional teams to help design intelligence derived strategies to detect fraud
Collaborate with fraud analytics modelling function to optimize anomaly detection capabilities
Develop new analytical solutions leveraging unstructured data sets and variables.

No preferred qualifications provided.