Quantitative Analyst, AVP Quantitative Analyst, AVP …

State Street Corporation
in Boston, MA, United States
Permanent, Full time
Be the first to apply
Competitive
State Street Corporation
in Boston, MA, United States
Permanent, Full time
Be the first to apply
Competitive
State Street Corporation
Quantitative Analyst, AVP
Quantitative Analyst, Assistant Vice President

BACKGROUND
The Centralized Modeling & Analytics (CMA) team within State Street's Enterprise Risk Management (ERM) organization is looking for an experienced quantitative analyst to join our team in Boston, MA.
The CMA organization provides analytics based services and solutions to business units across State Street. Our mission is to create value through data driven solutions enabling State Street and our business partners to make timely and informed decisions.

POSITION PRIMARY DUTIES AND RESPONSIBILITIES
This role will be part of the CMA team responsible for both financial and non-financial risk projection.
We provide support in the development, deployment, and documentation of tools and methods for assessing various aspects of credit, market, operational, liquidity and compliance risk to State Street.
This role will:
  • Build and enhance a variety of models or advanced analytical tools (e.g., liquidity, deposit, credit risk, interest rate risk) around different BAU purposes and regulations such as Basel III, CCAR and ICAAP
  • Creatively build analytical tool /models to assist non-financial risk analytics (e.g., operational risk, marketing analytics, AML and compliance analytics, etc.) using conventional and non-conventional techniques (e.g., AI, Machine Learning, Natural Language Processing)
  • Create actionable, automated reporting tools/packages to assist visualization of results, model implementation and quantitative analytics
  • Perform sensitivity analyses to respond to ad hoc inquiries
  • Perform any other tasks as assigned to support the CMA

REQUIREMENTS
  • Masters' or PhD in Economics, Statistics, Mathematics, Risk Management or related field
  • 3+ years of working experience in quantitative modeling as a key contributor
  • Ability to understand, visualize and communicate quantitative results to expert and non-expert audiences
  • 3+ years of experience with any of programming language using one or two of following: Python, R, Tableau, Excel and SQL with structured and non-structured data mart
  • Demonstratable experience with Natural Language Processing and Machine Learning techniques
  • Working understanding of various regulations such as Basel III (Credit/Market/Operational Risk), CCAR, Stress Testing and ICAAP
  • Working knowledge of fixed income market or wholesale credit market, from both quantitative credit or market risk experience
  • 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
  • Strong verbal and written communication skills, with ability to articulate ideas, analysis and complex concepts effectively to broad audiences
  • Competence and confidence to gain credibility and collaborate for success across the organization
  • Professional designations (CFA, FRM) preferred but not required
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.

State Street Corporation logo
More Jobs Like This
See more jobs
Close
Loading...
Loading...