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Quantitative Financial Analyst

Charlotte, North Carolina;

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
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.
The Enterprise Portfolio Analytics (EPA) team in Global Risk Analytics is a dynamic group that drives innovative concentration risk, portfolio surveillance using advanced analytics, and portfolio management strategies/techniques.
• Conducting quantitative analysis and market research that have critical impact to the Bank (e.g. impact of oil price decline, risk mitigation of rising USD)
• Preparing specialized content for high profile senior Risk, Line of Business, Board, and regulator requests
• Building connections between model driven analytics and practical risk/business applications (e.g. support LOB efforts for responsible growth)
• Developing actionable analytics and early warning indicators
• Develop dashboards to visualize the credit portfolio and recommend actions
• Help team develop and rollout new tools and functionality for portfolio informed analysis with respect to new business opportunities/strategies
• Help prepare and present training material of new concepts and capabilities for less quantitative audiences
• Identify and sponsor technical and data related enhancements as business champion
• Contribute to other special projects and initiatives as needs arise


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
• 2-3 years of relevant work experience. Master's Degree in Statistics, Economics, Computational Finance, Engineering, or related quantitative field.
• Ability to work in a large, complex organization, and influence various stakeholders and partners
• Self-starter; Initiates work independently, before being asked
• Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others
• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
• Effectively presents findings, data, and conclusions to influence senior leaders
• Ability to work in a highly controlled and audited environment
• Effective at prioritization, and time and project management
• Strong work ethic, ability to adapt to changing priorities and be team oriented


Desired Skills and Experience
• Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
• Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis
• Experience developing and maintaining complex databases and data sets
• Experience using data mining and other advanced analytical techniques to aggregate data for model development and/or to produce management reporting
• Experience with data visualization tools
• Experience managing large data sets utilizing tools such as Hadoop
• Experience with machine learning techniques, Web Scraping, numerical libraries e.g. Scikit-learn, Numpy, Pandas
• Experience with data analytics tools (e.g., Alteryx, Tableau, RShiny)
• Demonstrated ability to drive action and sustain momentum to achieve results
• Identifies, assigns, and manages project tasks and timelines across teams
• Demonstrated leadership skills; Ability to exert broad influence among peers
• Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow
• Sees the broader picture and is able to identify new methods for doing things
• Experience with LaTeX
• Comfort in programming languages (R/Python preferred)
• Advanced Excel, SQL, Hadoop, Alteryx and Tableau expertise
• Experience/ability to work on projects/initiatives with limited oversight

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
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.
The Enterprise Portfolio Analytics (EPA) team in Global Risk Analytics is a dynamic group that drives innovative concentration risk, portfolio surveillance using advanced analytics, and portfolio management strategies/techniques.
• Conducting quantitative analysis and market research that have critical impact to the Bank (e.g. impact of oil price decline, risk mitigation of rising USD)
• Preparing specialized content for high profile senior Risk, Line of Business, Board, and regulator requests
• Building connections between model driven analytics and practical risk/business applications (e.g. support LOB efforts for responsible growth)
• Developing actionable analytics and early warning indicators
• Develop dashboards to visualize the credit portfolio and recommend actions
• Help team develop and rollout new tools and functionality for portfolio informed analysis with respect to new business opportunities/strategies
• Help prepare and present training material of new concepts and capabilities for less quantitative audiences
• Identify and sponsor technical and data related enhancements as business champion
• Contribute to other special projects and initiatives as needs arise


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
• 2-3 years of relevant work experience. Master's Degree in Statistics, Economics, Computational Finance, Engineering, or related quantitative field.
• Ability to work in a large, complex organization, and influence various stakeholders and partners
• Self-starter; Initiates work independently, before being asked
• Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others
• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
• Effectively presents findings, data, and conclusions to influence senior leaders
• Ability to work in a highly controlled and audited environment
• Effective at prioritization, and time and project management
• Strong work ethic, ability to adapt to changing priorities and be team oriented


Desired Skills and Experience
• Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
• Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis
• Experience developing and maintaining complex databases and data sets
• Experience using data mining and other advanced analytical techniques to aggregate data for model development and/or to produce management reporting
• Experience with data visualization tools
• Experience managing large data sets utilizing tools such as Hadoop
• Experience with machine learning techniques, Web Scraping, numerical libraries e.g. Scikit-learn, Numpy, Pandas
• Experience with data analytics tools (e.g., Alteryx, Tableau, RShiny)
• Demonstrated ability to drive action and sustain momentum to achieve results
• Identifies, assigns, and manages project tasks and timelines across teams
• Demonstrated leadership skills; Ability to exert broad influence among peers
• Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow
• Sees the broader picture and is able to identify new methods for doing things
• Experience with LaTeX
• Comfort in programming languages (R/Python preferred)
• Advanced Excel, SQL, Hadoop, Alteryx and Tableau expertise
• Experience/ability to work on projects/initiatives with limited oversight

Shift:

1st shift (United States of America)

Hours Per Week: 

40

Learn more about this role

Full time

JR-21047708

Band: H5

Manages People: No

Travel: No

Manager:

Talent Acquisition Contact:

Jillian Teeter

Referral Bonus:

0