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Senior Quantitative Financial Manager

Chicago, Illinois;

Job Description:

Overview of Global Risk Analytics

Bank of America Merrill Lynch has an opportunity for a Senior Quantitative Finance Manager in 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:  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

Enterprise Risk Analytics is seeking a Senior Quantitative Finance Manager with a specialization in network science and econometric analysis for the Global Portfolio Strategies group to identify, model, and quantify Concentration Risk. The position will involve directing and managing other senior level staff in research and development projects requiring extensive knowledge of macroeconomics, banking, supplier networks, asset correlations, and quantitative finance. In addition, the manager will provide guidance and thought leadership to other senior level staff across Global Risk and Global Risk Analytics in area of expertise.

Role responsibilities may include:

  • Performing in-depth analysis on the Bank’s risk model results using various quantitative tools such as back testing, benchmarking, sensitivity analysis

  • Articulating the overall holistic picture of model performance, with clear conclusions regarding accuracy and remediation areas as required

  • Communicating model results to model stakeholders, including risk management, model development, model risk, senior management, and regulators

  • Supporting model development by confirming remediation of model issues prior to implementation

Required Education, Skills, and Experience

  • Advanced degree in Statistics, Economics, Data Science, Computational Finance, Network Science, or related field

  • 12+ years of relevant quantitative experience

  • 5+ of years of leadership/management experience

  • Strong econometrics and quantitative background

  • Excellent knowledge in macroeconomics, statistics, network science, and mathematics.

  • Deep understanding of network banking and correlated credit risk

  • Strong technical skills and problem solving ability.

  • Strong analytical mindset with accuracy to detail in work and ability to work with minimal supervision.

  • Exhibits flexibility with priorities, responsibilities and changing environments

  • Demonstrates commitment to excellence by anticipating needs, mitigating risks and minimizing potential problems.

  • Excellent written and oral communication

Desired Skills and Experience

  • Experience with coding in R/Python and data/analytical tools (Hadoop, SQL, Tableau)

  • Knowledge of banking products across Wholesale and Consumer lines of business

  • Experience in analyzing and presenting various facets of risk analytics including Stress Testing, Allowance, Scorecards, PD-LGD models, Capital (Economic and Regulatory) and Concentrations to senior management

  • Experience managing teams in the areas of advanced analytics (AI/ML/NLP) and BI/Visualization for effective communication of results.

  • Comfortable presenting to different stakeholders ranging from Risk, LOBs, Model Validation, and others

Job Band:

H3

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 Senior Quantitative Finance Manager in 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:  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

Enterprise Risk Analytics is seeking a Senior Quantitative Finance Manager with a specialization in network science and econometric analysis for the Global Portfolio Strategies group to identify, model, and quantify Concentration Risk. The position will involve directing and managing other senior level staff in research and development projects requiring extensive knowledge of macroeconomics, banking, supplier networks, asset correlations, and quantitative finance. In addition, the manager will provide guidance and thought leadership to other senior level staff across Global Risk and Global Risk Analytics in area of expertise.

Role responsibilities may include:

  • Performing in-depth analysis on the Bank’s risk model results using various quantitative tools such as back testing, benchmarking, sensitivity analysis

  • Articulating the overall holistic picture of model performance, with clear conclusions regarding accuracy and remediation areas as required

  • Communicating model results to model stakeholders, including risk management, model development, model risk, senior management, and regulators

  • Supporting model development by confirming remediation of model issues prior to implementation

Required Education, Skills, and Experience

  • Advanced degree in Statistics, Economics, Data Science, Computational Finance, Network Science, or related field

  • 12+ years of relevant quantitative experience

  • 5+ of years of leadership/management experience

  • Strong econometrics and quantitative background

  • Excellent knowledge in macroeconomics, statistics, network science, and mathematics.

  • Deep understanding of network banking and correlated credit risk

  • Strong technical skills and problem solving ability.

  • Strong analytical mindset with accuracy to detail in work and ability to work with minimal supervision.

  • Exhibits flexibility with priorities, responsibilities and changing environments

  • Demonstrates commitment to excellence by anticipating needs, mitigating risks and minimizing potential problems.

  • Excellent written and oral communication

Desired Skills and Experience

  • Experience with coding in R/Python and data/analytical tools (Hadoop, SQL, Tableau)

  • Knowledge of banking products across Wholesale and Consumer lines of business

  • Experience in analyzing and presenting various facets of risk analytics including Stress Testing, Allowance, Scorecards, PD-LGD models, Capital (Economic and Regulatory) and Concentrations to senior management

  • Experience managing teams in the areas of advanced analytics (AI/ML/NLP) and BI/Visualization for effective communication of results.

  • Comfortable presenting to different stakeholders ranging from Risk, LOBs, Model Validation, and others

Shift:

1st shift (United States of America)

Hours Per Week: 

40

Learn more about this role

Full time

JR-21016563

Band: H3

Manages People: Yes

Travel: Yes, 10% of the time

Manager:

Talent Acquisition Contact:

Jillian Teeter

Referral Bonus:

0