Head of Foundational Credit Risk Modeling, Managing Director (New York)

  • New York, NY


: $168,735.00 - $168,735.00 /year *

Employment Type

: Full-Time


: Financial Services - Insurance

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Pardon our dust! We are enhancing our application system to improve the Citi recruitment experience. Due to this upgrade you may be asked to create a new profile when you apply for a new job. If you submitted an application prior to July 21st you can view the status of your application and manage your documents via the Manage Existing link in the Create/Manage Profile drop down in the top right corner of this page. The Head of Foundational Credit Risk Modeling will lead a team of about 9 risk professionals located in New York and Tampa. The scope of work includes and is organized as follows: The Foundational Credit Risk Modeling team is responsible for life cycle development of fundamental models for loss likelihood and loss severity that support critical credit loss estimation for wholesale portfolios globally. The wholesale foundational models support credit loss estimation for credit reserves, including the Loan Loss Reserves, CECL and IFRS9 Accounting Standards; internal and regulatory stress testing, including GSST and CCAR/DFAST; and regulatory risk capital, including Basel requirements. The team also supports the organization and design of historical data on default events for wholesale portfolios needed to support the modeling efforts. Clients include Business, Finance, Risk Managers, Fundamental Credit Risk, Internal Audit, and others within Citi, as well as external auditors and regulators. Develop priorities for model development and related activities of the Team through engagement with partners in Risk, Finance and business units. Enhance the application of analytics within the Risk organization particularly in wholesale portfolio risk assessment for internal and regulatory purposes. Develop and implement industry-leading standards for model development and best-in-class analytics. Engage with Model Risk Management leadership to ensure that QRS model development and documentation practices meet MRM guidelines. Lead recruiting and training (including cross-training) initiatives in New York and Tampa. In addition to managing the Team, the Head of Foundational Credit Risk Modeling is relied on as a subject matter expert on Basel, CCAR and other regulatory rules that affect the estimation of credit loss likelihood and loss severity for wholesale products; and is often sought out as a thought-partner on the use of loss models for different applications and analysis for the business. Qualifications: MBA in Finance/Economics, Masters degree or PhD in a quantitative field (physics, mathematics, computer science, etc.), and 15 years of experience managing analytics teams in wholesale or retail credit risk modeling for loss likelihood and loss severity, and supporting business, auditors and regulators. Demonstrated knowledge of banking and credit products, credit risk and related regulatory rules. Experience leading advanced model development of wholesale or retail credit models of loss likelihood and loss severity, production implementation and business support. Experience integrating state-of-the-art modeling tools, big-data platforms and environments that can lead to cutting-edge innovative solutions. Experience in leading remote based teams is valuable but not essential. Track record of successfully hiring and mentoring talent. ---- Grade :All Job Level - All Job FunctionsAll Job Level - All Job Functions - US ---- Time Type :Full time ---- Citi is an equal opportunity and affirmative action employer.Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity. Citigroup Inc. and its subsidiaries (\"Citi) invite all qualified interested applicants to apply for career opportunities. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity CLICK HERE.

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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