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AVP, Python Programmer

Charlotte, North Carolina;

Job Description:

Overview of Global Risk Analytics 
Bank of America 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 Consumer Operations & GRA Strategy 

Consumer Operations & GRA Strategy is part of Global Risk Analytics (GRA). It is responsible for three primary bodies of work: strategic planning and delivery of major initiatives; program and project planning; and data management and model execution. 

•    Strategy and Major Initiatives are responsible for the planning and delivery of a coherent model risk management framework and infrastructure across GRA. These efforts include the development of one universal platform for seamless model development and implementation, and improvements to the quality and consistency of the data sourced for all development and production purposes. The team also provides forward-looking plans and solutions to ensure that GRA is addressing internal and regulatory requirements in a strategic, coordinated and pro-active manner. 
•    Programs and Projects provides project management oversight to key regulatory reviews such as the Current Expected Credit Losses (CECL) accounting standard and the Comprehensive Capital Analysis & Review (CCAR), as well as other strategic initiatives, including data, infrastructure and consumer model development. Additionally, the team ensures that technology roadmaps and data solutions align to Global Risk Management (GRM) strategies. 
•    Consumer Risk Analytics Data Management and Model Execution responsible for driving the delivery of complete, accurate, timely, and compliant data for the consumer models. The team also develops, executes and manages the consumer model production processes, which provides required outputs for both forecast administrators (FAs) and front line units (FLUs). 

Overview of the Role

As a Quantitative Finance Analyst within the GRA Strategy team, your main responsibilities will involve:
•    Implementing functionality to address requirements from users by building tools using Python on the strategic operating platform for use across GRA. 
•    Striving for Operational Excellence and ensuring tools developed are robust, generic, re-usable and modular to allow users from all areas in GRA to leverage developed tools. 
•    Reviewing code developed by others
•    Striving for excellence in code quality, testing, documentation, and design
•    Working closely with a variety of stakeholders, including model development, production operations and technology to deliver a best-in-class product for risk management purposes, process automation and usability
•    Proactively identifying risks and improvements to existing processes and technology architecture

Required Education, Skills and Experience

•    Masters in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline
•    5+ years professional experience
•    Must have Python Programming experience

•   Expertise in creating data processes and managing those process

•   Python programming specialized in Data / Data engineering

•    Experience managing large data sets utilizing tools such as Hadoop
•    Strong analytical and problem-solving skills

•    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
•    Ability to work in a highly controlled and audited environment


Desired Skills and Experience

•    Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
•    Experience with data analytics tools (e.g., Alteryx, Tableau)
•    Experience building data architecture that is optimized for large dataset retrieval, analysis, storage, cleansing, and transformation
•    Demonstrated ability to drive action and sustain momentum to achieve results
•    Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow

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 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 Consumer Operations & GRA Strategy 

Consumer Operations & GRA Strategy is part of Global Risk Analytics (GRA). It is responsible for three primary bodies of work: strategic planning and delivery of major initiatives; program and project planning; and data management and model execution. 

•    Strategy and Major Initiatives are responsible for the planning and delivery of a coherent model risk management framework and infrastructure across GRA. These efforts include the development of one universal platform for seamless model development and implementation, and improvements to the quality and consistency of the data sourced for all development and production purposes. The team also provides forward-looking plans and solutions to ensure that GRA is addressing internal and regulatory requirements in a strategic, coordinated and pro-active manner. 
•    Programs and Projects provides project management oversight to key regulatory reviews such as the Current Expected Credit Losses (CECL) accounting standard and the Comprehensive Capital Analysis & Review (CCAR), as well as other strategic initiatives, including data, infrastructure and consumer model development. Additionally, the team ensures that technology roadmaps and data solutions align to Global Risk Management (GRM) strategies. 
•    Consumer Risk Analytics Data Management and Model Execution responsible for driving the delivery of complete, accurate, timely, and compliant data for the consumer models. The team also develops, executes and manages the consumer model production processes, which provides required outputs for both forecast administrators (FAs) and front line units (FLUs). 

Overview of the Role

As a Quantitative Finance Analyst within the GRA Strategy team, your main responsibilities will involve:
•    Implementing functionality to address requirements from users by building tools using Python on the strategic operating platform for use across GRA. 
•    Striving for Operational Excellence and ensuring tools developed are robust, generic, re-usable and modular to allow users from all areas in GRA to leverage developed tools. 
•    Reviewing code developed by others
•    Striving for excellence in code quality, testing, documentation, and design
•    Working closely with a variety of stakeholders, including model development, production operations and technology to deliver a best-in-class product for risk management purposes, process automation and usability
•    Proactively identifying risks and improvements to existing processes and technology architecture

Required Education, Skills and Experience

•    Masters in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline
•    5+ years professional experience
•    Must have Python Programming experience

•   Expertise in creating data processes and managing those process

•   Python programming specialized in Data / Data engineering

•    Experience managing large data sets utilizing tools such as Hadoop
•    Strong analytical and problem-solving skills

•    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
•    Ability to work in a highly controlled and audited environment


Desired Skills and Experience

•    Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
•    Experience with data analytics tools (e.g., Alteryx, Tableau)
•    Experience building data architecture that is optimized for large dataset retrieval, analysis, storage, cleansing, and transformation
•    Demonstrated ability to drive action and sustain momentum to achieve results
•    Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow

Shift:

1st shift (United States of America)

Hours Per Week: 

40

Learn more about this role

Full time

JR-22014048

Band: H5

Manages People: No

Travel: No

Manager:

Talent Acquisition Contact:

Pamela Salvato

Referral Bonus:

0