- Joined
- 9/23/14
- Messages
- 3
- Points
- 11
Name of Employer or Agency
BNY Mellon
Job title
Sr. Quantitative Risk Analyst
Location
Pittsburgh, PA or New York City
Job description
This position is responsible for developing, maintaining and validating risk models for quantifying various types of financial risks (such as operation risk, credit risk, market risk and interest rate risk) inherent in the Corporation's business activities and processes. These models calculate values at risk or economic capitals that are reported to Senior Management and the Board of Directors on a regular basis as a key input to risk management decision making. Models must use methodologies that are theoretically sound, with modeling choices, assumptions and parameters that are justifiable and supportable. The incumbent ensures that model development, implementation, data input, reporting, documentation, validation and maintenance use best practices, adhere to consistency and quality standards, and follow the guidance of corporate policies and procedures and regulatory requirements. Incumbent provides intellectual leadership in terms of conducting cutting-edge research, identifying latest trends and developments in financial risk modeling, and recommending solutions to analytically challenging problems.
The candidate must have a superb quantitative and analytical background with a solid theoretical foundation coupled with strong programming, documentation and communications skills. Must have a Master's Degree/PhD preferred (e.g., mathematics, physics, statistics or engineering); at least 6-8 years of academic/industry experience in complex quantitative modeling; experience in numerical analysis and computational methods using programming languages (such as C/C++, C#, Java, FORTRAN, MATLAB, SAS) and mathematical/statistical software packages. Must be extremely focused, detail oriented, results oriented and highly productive. Must have a proven track record of being able to efficiently and effectively conduct independent research, analyze problems, formulate and implement solutions, and produce quality results on time. The candidate must have excellent scientific and technical documentation and presentation skills, assertiveness & influencing skills, and the skills to explain abstract theoretical concepts to a non-expert audience in easy-to-understand language.
Apply/contact info for candidates
http://jobs.bnymellon.com/job/Pittsburgh-Sr-Quantitative-Risk-Analyst-Job-PA-15122/57533200/
Employer profile
BNY Mellon is a global investments company dedicated to helping its clients manage and service their financial assets throughout the investment lifecycle. Whether providing financial services for institutions, corporations or individual investors, BNY Mellon delivers informed investment management and investment services in 35 countries and more than 100 markets. BNY Mellon can act as a single point of contact for clients looking to create, trade, hold, manage, service, distribute or restructure investments. Additional information is available at www.bnymellon.com.
BNY Mellon
Job title
Sr. Quantitative Risk Analyst
Location
Pittsburgh, PA or New York City
Job description
This position is responsible for developing, maintaining and validating risk models for quantifying various types of financial risks (such as operation risk, credit risk, market risk and interest rate risk) inherent in the Corporation's business activities and processes. These models calculate values at risk or economic capitals that are reported to Senior Management and the Board of Directors on a regular basis as a key input to risk management decision making. Models must use methodologies that are theoretically sound, with modeling choices, assumptions and parameters that are justifiable and supportable. The incumbent ensures that model development, implementation, data input, reporting, documentation, validation and maintenance use best practices, adhere to consistency and quality standards, and follow the guidance of corporate policies and procedures and regulatory requirements. Incumbent provides intellectual leadership in terms of conducting cutting-edge research, identifying latest trends and developments in financial risk modeling, and recommending solutions to analytically challenging problems.
The candidate must have a superb quantitative and analytical background with a solid theoretical foundation coupled with strong programming, documentation and communications skills. Must have a Master's Degree/PhD preferred (e.g., mathematics, physics, statistics or engineering); at least 6-8 years of academic/industry experience in complex quantitative modeling; experience in numerical analysis and computational methods using programming languages (such as C/C++, C#, Java, FORTRAN, MATLAB, SAS) and mathematical/statistical software packages. Must be extremely focused, detail oriented, results oriented and highly productive. Must have a proven track record of being able to efficiently and effectively conduct independent research, analyze problems, formulate and implement solutions, and produce quality results on time. The candidate must have excellent scientific and technical documentation and presentation skills, assertiveness & influencing skills, and the skills to explain abstract theoretical concepts to a non-expert audience in easy-to-understand language.
Apply/contact info for candidates
http://jobs.bnymellon.com/job/Pittsburgh-Sr-Quantitative-Risk-Analyst-Job-PA-15122/57533200/
Employer profile
BNY Mellon is a global investments company dedicated to helping its clients manage and service their financial assets throughout the investment lifecycle. Whether providing financial services for institutions, corporations or individual investors, BNY Mellon delivers informed investment management and investment services in 35 countries and more than 100 markets. BNY Mellon can act as a single point of contact for clients looking to create, trade, hold, manage, service, distribute or restructure investments. Additional information is available at www.bnymellon.com.
Last edited by a moderator:
