Quantitative Analyst, Officer Quantitative Analyst, Officer …

State Street Corporation
in Boston, MA, United States
Permanent, Full time
Last application, 28 Mar 20
State Street Corporation
in Boston, MA, United States
Permanent, Full time
Last application, 28 Mar 20
State Street Corporation
Quantitative Analyst, Officer
Job Description Quantitative Analyst, Officer

State Street Corporation (NYSE: STT) is the world's leading provider of financial services to institutional investors including investment servicing, investment management and investment research and trading. With $30+ trillion in assets under custody and administration and $2+ trillion in assets under management, State Street operates globally in more than 100 geographic markets and employs more than 30,000 worldwide. For more information, visit State Street's website at http://www.statestreet.com/.

State Street Corporation's Model Validation Group (MVG) is recruiting for Quantitative Analysts at the junior level. MVG is part of the broader Model Risk Management function that is responsible for the identification, measurement, and mitigation of model risk across the global enterprise.

The work of Quantitative Analysts will be guided by Senior Quantitative Analysts who lead model reviews. MVG's review work is focused on models used to make business and operating decisions. The models are diverse, many can be classified as belonging to the following general areas: wholesale credit risk (e.g., probability of default, loss given default); market risk (e.g., daily Value at Risk pricing models and ALM risk); securities finance; asset management; budgeting, taxation and financial planning, and operational risk.

Specific tasks performed during model reviews include but are not limited to:
  • Assessing model theory and model assumptions as well as considering model methods and alternate options.
  • Testing and confirming model results by using documented procedures for running the models.
  • Reviewing code documentation for proper model implementation, including the possible simulation of results.
  • Working with data validation members and information technology professionals to assess model data integrity.
  • Performing model validation processes and performing independent model validation of significant models.
  • Assessing the stability and robustness of models by conducting backtesting, sensitivity testing, and stress testing.
  • Making recommendations and suggesting improvements related to the applicability of the different models assessed in meeting their objectives.
  • Master in Finance, Economics, Mathematics, Statistics, and/or other quantitative discipline. Exceptional candidates with a Bachelor's degree and 3+ years of relevant work experience will also be considered.
  • Work experience in a Financial Services Firm preferred. Model Validation experience a plus.
  • Excellent quantitative modeling, analytical, research, and programming skills (e.g., SAS, Matlab, Stata, SQL, VBA, and/or C++) required.
  • Strong communication skills both verbal and written.
  • Good project management skills, with the ability to work independently on multiple tasks and/or projects.
  • Knowledge of financial markets and products.
  • The candidate must be able to take initiative and meet deadlines.
Company Overview

From technology and product innovation to corporate responsibility and community development, we're making our mark on the financial services industry. For more than two centuries, we've been helping our clients safeguard and steward the investments of millions of people - strengthening markets, building communities and creating opportunities for growth.

We owe that longevity to the commitment, expertise and creativity of our employees. Our continued success depends on our ability to attract and develop the best talent in the industry. That's why we're keenly focused on employee development, corporate citizenship and inclusion.

For us, success comes in the mark we make as an organization - for the industry, our clients, our communities and each other.