CONTD FROM H.10B performing data modeling, integration, and mining in the financial services industry, using SQL, R, and Python.br br Education and Experiencebr br Bachelors degree or foreign education equivalent in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and three 3 years of experience in the job offered or three 3 years of experience performing data modeling, integration, and mining in the financial services industry, using SQL, R, and Python.br br Or, alternatively, Masters degree or foreign education equivalent in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and one 1 year of experience in the job offered or one 1 year of experience performing data modeling, integration, and mining in the financial services industry, using SQL, R, and Python.br br Skills and Knowledgebr br Candidate must also possessbr br Demonstrated Expertise DE designing and developing data pipelines for data warehouses, using ETL tools Informatica PowerCenter and Alteryx and integrating the data pipelines with external PLSQL, Python, and UNIX Shell scripting; creating and managing batch jobs, using Autosys and Informatica servers; and identifying bottlenecks in extract, transform, load ETL packages and providing best suited solutions;br br DE designing and developing data models and databases to ensure interoperability with BI solutions using PLSQL; writing triggers, cursors, PLSQL stored procedures, packages, and complex transactional SQL queries within DB2, Sybase, Netezza, Hadoop, SQL Server, and Oracle databases; performing database management and capacity planning on Oracle and DB2 databases using SQL queries; and creating corrective measures by identifying performance issues using SQL queries;br br DE performing data profiling, mining, specification, extraction, cleansing, and analysis for large data warehouses, using DB2, Sybase, Netezza, Hadoop, SQL Server, and Oracle; and generating visual insights for business and end users, using Oracle Business Intelligence Enterprise Edition OBIEE, BI Publisher, and Tableau;br br DE detecting cyber and noncyber financial services fraud events identifying risk and threat vectors, assessing current customer protection controls, and determining opportunities for implementation of solutions to prevent financial fraud on customer accounts.
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