Risk Policy Senior Analyst

4 days ago


Wilmington, Delaware, United States Citigroup Inc Full time
About the Role

This position is within the Collections Risk Policy Team, part of the Citi Retail Services Risk Management team. The Collections and Recovery Risk team's mission is to help customers bring their accounts current or fairly resolve their debt. The Collections Policy team owns Policy and Strategy, and partners closely with the Operations and Technology teams on implementation and execution.

Key Responsibilities
  • Manage the US Cards Collections policy, ensuring compliance to Citi Global Risk policies and Legal Regulations.
  • Develop and analyze customer risk strategies and segmentation schemes, profiling of segments as well as reporting and tracking (MIS) of performance.
  • Represent risk management through the development life cycle of a new strategy or policy.
  • Build robust inventory of internal and external data sources to enhance policy development and advanced analytical capabilities in the Collections space.
  • Contribute to the development of analytical tools used in the assessment of collections risk and policy.
Requirements
  • 5-8 years experience in Statistics/Analytics/Decision Management.
  • Effective negotiation skills, a proactive and 'no surprises' approach in communicating Risk issues.
  • Management Capability.
  • Able to make decisions on matters pertaining to aspects of risk, especially on credit risk.
  • Able to identify and influence key decision makers across various levels and functions within the organization.
  • Able to work in a rapidly changing external environment and support business in a highly competitive and challenging market.
Education
  • Bachelor's degree in a quantitative discipline: Mathematics, Economics, Operations Research, Statistics.
  • Master's degree in a quantitative discipline preferred.
Skills
  • Strong analytical skills in conducting sophisticated analysis using customer performance data, bureau data, and marketing data to solve business problems.
  • Excellent programming skills in advanced SAS and SQL.
  • Experience in advanced analytics utilizing Python / R in a Big Data environment preferred.
  • Highly proficient in Excel/pivot tables and PowerPoint.


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