Market Risk, VP

at  State Street

Overview
Centralized Modeling, Analytics and Operations (CMAO), a team within State Street’s Enterprise Risk Management (ERM) department, is looking for an experienced and highly motivated professional with strong quantitative, problem-solving, and communication skills. The primary focus for the position will be to develop quantitative models and tools to assess and analyze risks associated with State Street’s investment portfolio which consists of various fixed income securities.
Position Duties and Responsibilities
The individual must have hands-on experience in quantitative modeling with strong programming skills in Python and R, and possess excellent verbal and written communication skills for interactions within CMAO as well as with internal and external stakeholders including global business partners (e.g. GT business partners, internal and external auditors), and regulators.

Primary Responsibilities

• The quantitative analyst is expected to utilize advanced quantitative skills to develop interest rate risk, credit risk and liquidity risk models by directly linking macroeconomic factors to key credit risk drivers for various asset classes held in the investment portfolio
• 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
• Implementing model in Python/R in a controlled environment
• Providing support on special projects, including review, oversight and analysis to support key strategic risk-related initiatives
• Ensuring appropriate reporting and governance exists to communicate relevant risk information to senior management
• Generating monthly or quarterly risk reporting

Qualifications

• Master’s degree or PhD degree in quantitative discipline
• At least 5 years of quantitative modeling experience in a financial institution
• In-depth understanding of statistics, econometrics, multivariate regressions, machine learning and other quantitative finance topics
• Advanced proficiency in using Python and R to perform large dataset analysis and build quantitative models
• Solid knowledge in financial markets and fixed income products
• Demonstrated experience in credit risk management, interest rate risk and/or asset liability management.
• Working knowledge in QRM is a plus
• 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 manage projects/key stake holders 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
• Ownership mindset is a must

Salary Range:
$120,000 - $195,000 Annual
The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ

• The quantitative analyst is expected to utilize advanced quantitative skills to develop interest rate risk, credit risk and liquidity risk models by directly linking macroeconomic factors to key credit risk drivers for various asset classes held in the investment portfolio
• 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
• Implementing model in Python/R in a controlled environment
• Providing support on special projects, including review, oversight and analysis to support key strategic risk-related initiatives
• Ensuring appropriate reporting and governance exists to communicate relevant risk information to senior management
• Generating monthly or quarterly risk reportin