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The Model/Anlys/Valid Intmd Anlyst is a developing professional role responsible for risk analysis, development and validation of risk measurement methods, compliance reviews, and reporting within Citi's Risk Management team.
Job Responsibility:
Develops, enhances, and validates the methods of measuring and analyzing risk, for all risk types including market, credit and operational
Supports the design, development, delivery and maintenance of best-in-class Risk programs, policies and practices for Risk Management
Reviews institutional or retail analytics and Models and other documents to ensure compliance with various regulatory and legal requirements
Identifies potential risks and escalates for further review
Handles preliminary investigations, assists with reconciliation procedures and prepares routine correspondence
Creates and maintains reports for control, tracking, and analysis purposes and ensures appropriate and secure retention of documents
Works with more senior staff in investigating and responding to customer and operational complaints
Interacts and works with other areas within Risk Management, as necessary
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency
Requirements:
4+ years' experience
Proficient in Microsoft Office with an emphasis on MS Excel
Proficiency in data analysis and visualization tools such as Python and Tableau
Consistently demonstrates clear and concise written and verbal communication skills
Self-motivated and detail oriented
Demonstrated project management and organizational skills and capability to handle multiple projects at one time
Bachelor’s/University degree or equivalent experience in a quantitative discipline: Statistics, Mathematics, Economics, Econometrics, Management, Operations Research or Engineering
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