Grade ( relevant for internal applicants only ): 11
The Location: Chicago (only will consider candidates in Chicago or open to relocating to Chicago)
The Team: The Associate - Model Validation (Senior Analyst, Quantitative Modeling) is a member of a model validation team which independently validates (tests) the quantitative financial models and engines that are developed throughout S&P Global Ratings. The Associate will support the model validation process for the full life cycle of S&P Global Ratings models. The Associate will be responsible for reviewing developmental evidence, conducting model replication and back-testing, and verifying that the models being reviewed are appropriate implementations of the relevant S&P Global Ratings Criteria. The Associate will utilize Excel, MATLAB, C++, R, Python or SAS to complete their assigned tasks on a timely basis. This position requires regular interaction with internal clients in S&P Global Ratings.
Compensation/Benefits Information (US Applicants Only):
S&P Global states that the anticipated base salary range for this position is $83,200 to $190,100. Base salary ranges may vary by geographic location.
In addition to base compensation, this role is eligible for an annual incentive plan.
Interact with quantitative staff to gather model related information and clarify model related questions
Interact with business unit staff to gather model related information and clarify model related questions
Communicate findings and recommendations with Ratings Quality and Ratings Business
Enhance procedures for model validation to meet new standards
Advanced degree in Economics, Mathematics, Statistics, Quantitative/Mathematical Finance or a closely related discipline (Masters or Ph.D.).
1+ years of experience in quantitative financial research, model development and model validation.
Good quantitative financial knowledge in the areas of stochastic interest rate modeling, prepayment modeling, spread modeling, default modeling and cash flow modeling.
Good quantitative skills in the areas of structured finance, credit derivatives, default and recovery modeling and credit risk management.
In-depth knowledge of structured financial instruments (CDO, CMBS, ABS, RMBS) as well as corporate finance and capital adequacy for financial institutions desirable.
Good programming skills in SAS, MATLAB, C++, R or Python.
Strong ability to communicate complex technical results to non-quantitative audience.
Ability to work independently
Excellent communication and interpersonal skills.
About S&P Global Ratings
S&P Global Ratings is the world's leading provider of independent credit ratings. Our ratings are essential to driving growth, providing transparency and helping educate market participants so they can make decisions with confidence. We have more than 1 million credit ratings outstanding on government, corporate, financial sector and structured finance entities and securities. We offer an independent view of the market built on a unique combination of broad perspective and local insight. We provide our opinions and research about relative credit risk; market participants gain independent information to help support the growth of transparent, liquid debt markets worldwide.
S&P Global Ratings is a division of S&P Global (NYSE: SPGI), which provides essential intelligence for individuals, companies and governments to make decisions with confidence. For more information, visit www.spglobal.com/ratings.
Equal Opportunity Employer:
S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.
If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.