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Job Description OVERVIEW Global Treasury Risk Management (GTRM), a team within State Street's Enterprise Risk Management (ERM) department, is looking for an experienced quantitative modeling professional. The primary focus for the position will be developing or working with vendors to develop macro-economic driven credit loss estimation models for commercial and/or consumer assets. THE COMPANY State Street Corporation (NYSE: STT) is one of the world`s leading providers of financial services to institutional investors including investment servicing, investment management and investment research and trading. With $28 trillion assets under custody and administration and $2 trillion assets under management at December 31, 2015, State Street operates in more than 100 geographic markets and employs 32,000 people worldwide. GLOBAL TREASURY RISK MANAGEMENT OVERSIGHT Banking is a risk-taking business. The goal of ERM is to ensure that State Street's risks are proactively identified, well-understood, and prudently managed in support of our business strategy. As such, ERM provides risk oversight, support, and coordination to ensure consistent identification, measurement and management of all risks possible in providing products and services to our clients. GTRM acts as the business-aligned risk function focused on these responsibilities for the activities of the Global Treasury (GT) department, inclusive of the Credit Risk Management team. State Street Treasury's mission is sustainable growth in net interest revenue driven by the monetization of liabilities from custody clients and the overall management of the corporation's balance sheet, while managing risk consistent with the company's risk appetite and regulatory constraints. GT core functions include managing the investment portfolio, asset-liability risk, liquidity risk, funding and liability pricing, capital structure, and rating agency relationships.The Global Treasury Management team is responsible for the portfolio credit risk oversight and control of the global investment portfolio, including other-than-temporary-impairment assessment, bottom-up stress tests, credit risk measurement and analytics, concentration risk measurement and monitoring, portfolio credit limits monitoring and approval/exception analysis, SFA/SSFA modeling, as well as various regulatory and management reporting. POSITION PRIMARY DUTIES AND RESPONSIBILITIES The Quantitative Analyst, AVP is a Boston, MA-based position in GTRM. This individual must have some experience in quantitative modeling and possess excellent verbal and written communication skills for interactions within GTRM as well as with internal and external stakeholders including global business partners (e.g. GT business partners, internal and external auditor), and regulators. The person should be prepared to use vended tools as well as to develop internal models, both for primary analysis as well as benchmarking. Primary responsibilities include:
- Managing and manipulating large and complex data sets using advanced statistical tools, including data cleaning, representativeness testing, etc.
- The quantitative analyst is expected to utilize advanced quantitative techniques to develop credit loss estimation models by directly linking macroeconomic factors to key credit risk drivers based on historical time series data
- Documenting, defending, and conducting ongoing monitoring of model performance through advanced statistical testing and sensitivity analysis
- Writing clear technical documentation as well as presenting and defending results to independent Model Validation team, senior management, and regulators
- Collaborating with business partners in the model development process
- Working with the information technology group to document business requirements and to ensure methodologies are accurately implemented in production systems
- Completing ad hoc assignments as needed
- Provide quantitative support for the global treasury risk management team
Qualifications Qualifications / Requirements:
- Master's or PhD degree in quantitative discipline
- At least 2-5 years of quantitative modeling aptitude/experience in a large, complex financial institution
- In-depth understanding of multivariate regressions and time series econometrics
- Good understanding of either consumer and/or commercial markets;
- Advanced proficiency in statistical modeling languages such as SAS, Matlab, R, Stata, or C++
- Ability to communicate complex concepts to broad audiences, with strong verbal and written communication skills
- A demonstrated ability to work independently on complex projects as well as the ability to be a team player in a fast-paced, high-energy level environment
- Competence and confidence to gain credibility and collaborate for success across the organization.
- Results oriented. Willingness to work in a position with uneven and high priority project work
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