Quantitative Finance Analyst

at Merrill Lynch
Location Chicago, IL
Date Posted September 26, 2021
Category Default
Job Type Full-time

Description

Job Description:

Overview of Global Risk Analytics
Bank of America Merrill Lynch has an opportunity for a Quantitative Finance Analyst (B5) within our Global Risk Analytics (GRA) function. GRA is a sub-line of business within Global Risk Management (GRM). GRA is responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across Bank of America.

GRA partners with the Lines of Business and Enterprise functions to ensure that its models and analytics address both internal and regulatory requirements, such as quarterly Enterprise Stress Testing (EST), the annual Comprehensive Capital Analysis and Review (CCAR), and the Current Expected Credit Losses (CECL) accounting standard. GRA models follow an iterative and ongoing development life cycle, as the bank responds to the changing nature of portfolios, economic conditions and emerging risks.

In addition to model development, GRA conducts model implementation, data management, model execution and analysis, forecast administration, and model performance monitoring. GRA drives innovation, process improvement and automation across all of these activities.

Overview of the Team
Overview of Enterprise Risk Analytics
As a part of Global Risk Analytics (GRA), Enterprise Risk Analytics (ERA) is responsible for the development of cross-business holistic analytical models and tools.

ERA consists of the following teams:
• Economic Scenario Generation (ESG) provides consistent and granular scenario generation capabilities for economic and market variables that enable multiple “what-if” outcomes for government regulators and other business uses.
• Enterprise Portfolio Analytics (EPA) provides portfolio surveillance visualization tools, utilizing advanced analytics (artificial intelligence/machine learning/natural language processing), to provide decision making support around the credit cycle, geo-intelligence, and thematic “what-if” analyses. EPA’s tools also support Enterprise strategic risk appetite and limits decisions for the bank’s risk and capital frameworks.
• Concentration Risk provides capital estimates to support annual regulatory requirements and legal entity-level capital management using tools and techniques focused on identification, measurement, and mitigation of concentration risks across countries, regions, sectors, and industries.
• Enterprise Capital Risk Analytics manages model performance monitoring and capital model issue resolution.
• Compliance Modelling & Analytics supports Enterprise needs around Fair Lending and Global Financial Crimes Compliance.
• Central Quantitative Group (CQG) provides sophisticated quantitative solutions for ERA clients. The group often partners with other teams within and outside GRA to provide these solutions.

Overview of the Role
As a Quantitative Finance Analyst on the Enterprise Risk Analytics team, your main responsibilities will involve:
• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements
• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks
• Understanding and executing activities that form the end-to-end model development and use life cycle
• Clearly documenting and effectively communicating quantitative methods as part of ongoing engagement with key stakeholders, including the lines of business, risk managers, model validation, technology

Position Overview
• Responsible for independently conducting quantitative analytics and modeling projects.

• Responsible for developing new models, analytic processes or systems approaches.

• Creates documentation for all activities and works with Technology staff in design of any system to run models developed.

• Incumbents possess excellent quantitative/analytic skills and a broad knowledge of financial markets and products.

Required Education, Skills, and Experience
• Graduate degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)
• 2+ years of experience in model development, statistical work, data analytics or quantitative research or PhD
• Strong Programming skills e.g. R, Python, SAS, SQL or other languages
• Strong analytical and problem-solving skills

Desired Skills and Experience
• Knowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniques
• Strong technical writing, communication and presentation skills and ability to effectively communicate quantitative topics with non-technical audiences
• Experience with large data sets
• Effective at prioritization/time and project management
• Broad understanding of financial products

Job Band:

H5

Shift: 

1st shift (United States of America)

Hours Per Week:

40

Weekly Schedule:

Referral Bonus Amount:

0 -->

Job Description:

Overview of Global Risk Analytics
Bank of America Merrill Lynch has an opportunity for a Quantitative Finance Analyst (B5) within our Global Risk Analytics (GRA) function. GRA is a sub-line of business within Global Risk Management (GRM). GRA is responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across Bank of America.

GRA partners with the Lines of Business and Enterprise functions to ensure that its models and analytics address both internal and regulatory requirements, such as quarterly Enterprise Stress Testing (EST), the annual Comprehensive Capital Analysis and Review (CCAR), and the Current Expected Credit Losses (CECL) accounting standard. GRA models follow an iterative and ongoing development life cycle, as the bank responds to the changing nature of portfolios, economic conditions and emerging risks.

In addition to model development, GRA conducts model implementation, data management, model execution and analysis, forecast administration, and model performance monitoring. GRA drives innovation, process improvement and automation across all of these activities.

Overview of the Team
Overview of Enterprise Risk Analytics
As a part of Global Risk Analytics (GRA), Enterprise Risk Analytics (ERA) is responsible for the development of cross-business holistic analytical models and tools.

ERA consists of the following teams:
• Economic Scenario Generation (ESG) provides consistent and granular scenario generation capabilities for economic and market variables that enable multiple “what-if” outcomes for government regulators and other business uses.
• Enterprise Portfolio Analytics (EPA) provides portfolio surveillance visualization tools, utilizing advanced analytics (artificial intelligence/machine learning/natural language processing), to provide decision making support around the credit cycle, geo-intelligence, and thematic “what-if” analyses. EPA’s tools also support Enterprise strategic risk appetite and limits decisions for the bank’s risk and capital frameworks.
• Concentration Risk provides capital estimates to support annual regulatory requirements and legal entity-level capital management using tools and techniques focused on identification, measurement, and mitigation of concentration risks across countries, regions, sectors, and industries.
• Enterprise Capital Risk Analytics manages model performance monitoring and capital model issue resolution.
• Compliance Modelling & Analytics supports Enterprise needs around Fair Lending and Global Financial Crimes Compliance.
• Central Quantitative Group (CQG) provides sophisticated quantitative solutions for ERA clients. The group often partners with other teams within and outside GRA to provide these solutions.

Overview of the Role
As a Quantitative Finance Analyst on the Enterprise Risk Analytics team, your main responsibilities will involve:
• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements
• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks
• Understanding and executing activities that form the end-to-end model development and use life cycle
• Clearly documenting and effectively communicating quantitative methods as part of ongoing engagement with key stakeholders, including the lines of business, risk managers, model validation, technology

Position Overview
• Responsible for independently conducting quantitative analytics and modeling projects.

• Responsible for developing new models, analytic processes or systems approaches.

• Creates documentation for all activities and works with Technology staff in design of any system to run models developed.

• Incumbents possess excellent quantitative/analytic skills and a broad knowledge of financial markets and products.

Required Education, Skills, and Experience
• Graduate degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)
• 2+ years of experience in model development, statistical work, data analytics or quantitative research or PhD
• Strong Programming skills e.g. R, Python, SAS, SQL or other languages
• Strong analytical and problem-solving skills

Desired Skills and Experience
• Knowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniques
• Strong technical writing, communication and presentation skills and ability to effectively communicate quantitative topics with non-technical audiences
• Experience with large data sets
• Effective at prioritization/time and project management
• Broad understanding of financial products

Job Band:

H5

Shift: 

1st shift (United States of America)

Hours Per Week:

40

Weekly Schedule:

Referral Bonus Amount:

0

Job Description:
Overview of Global Risk Analytics
Bank of America Merrill Lynch has an opportunity for a Quantitative Finance Analyst (B5) within our Global Risk Analytics (GRA) function. GRA is a sub-line of business within Global Risk Management (GRM). GRA is responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across Bank of America.

GRA partners with the Lines of Business and Enterprise functions to ensure that its models and analytics address both internal and regulatory requirements, such as quarterly Enterprise Stress Testing (EST), the annual Comprehensive Capital Analysis and Review (CCAR), and the Current Expected Credit Losses (CECL) accounting standard. GRA models follow an iterative and ongoing development life cycle, as the bank responds to the changing nature of portfolios, economic conditions and emerging risks.

In addition to model development, GRA conducts model implementation, data management, model execution and analysis, forecast administration, and model performance monitoring. GRA drives innovation, process improvement and automation across all of these activities.

Overview of the Team
Overview of Enterprise Risk Analytics
As a part of Global Risk Analytics (GRA), Enterprise Risk Analytics (ERA) is responsible for the development of cross-business holistic analytical models and tools.

ERA consists of the following teams:
• Economic Scenario Generation (ESG) provides consistent and granular scenario generation capabilities for economic and market variables that enable multiple “what-if” outcomes for government regulators and other business uses.
• Enterprise Portfolio Analytics (EPA) provides portfolio surveillance visualization tools, utilizing advanced analytics (artificial intelligence/machine learning/natural language processing), to provide decision making support around the credit cycle, geo-intelligence, and thematic “what-if” analyses. EPA’s tools also support Enterprise strategic risk appetite and limits decisions for the bank’s risk and capital frameworks.
• Concentration Risk provides capital estimates to support annual regulatory requirements and legal entity-level capital management using tools and techniques focused on identification, measurement, and mitigation of concentration risks across countries, regions, sectors, and industries.
• Enterprise Capital Risk Analytics manages model performance monitoring and capital model issue resolution.
• Compliance Modelling & Analytics supports Enterprise needs around Fair Lending and Global Financial Crimes Compliance.
• Central Quantitative Group (CQG) provides sophisticated quantitative solutions for ERA clients. The group often partners with other teams within and outside GRA to provide these solutions.

Overview of the Role
As a Quantitative Finance Analyst on the Enterprise Risk Analytics team, your main responsibilities will involve:
• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements
• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks
• Understanding and executing activities that form the end-to-end model development and use life cycle
• Clearly documenting and effectively communicating quantitative methods as part of ongoing engagement with key stakeholders, including the lines of business, risk managers, model validation, technology

Position Overview
• Responsible for independently conducting quantitative analytics and modeling projects.

• Responsible for developing new models, analytic processes or systems approaches.

• Creates documentation for all activities and works with Technology staff in design of any system to run models developed.

• Incumbents possess excellent quantitative/analytic skills and a broad knowledge of financial markets and products.

Required Education, Skills, and Experience
• Graduate degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)
• 2+ years of experience in model development, statistical work, data analytics or quantitative research or PhD
• Strong Programming skills e.g. R, Python, SAS, SQL or other languages
• Strong analytical and problem-solving skills

Desired Skills and Experience
• Knowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniques
• Strong technical writing, communication and presentation skills and ability to effectively communicate quantitative topics with non-technical audiences
• Experience with large data sets
• Effective at prioritization/time and project management
• Broad understanding of financial products
Shift:

1st shift (United States of America)

Hours Per Week: 

40