Quantitative Engineer jobs at Bank Of America in United States, Charlotte

This job is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key responsibilities include developing new models, analytic processes, or systems approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations include having a broad knowledge of financial markets and products.

Responsibilities:

• Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers

• Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization

• Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation

• Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite

• Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk

• Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes

• Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches

Overview of Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT)

Bank of America Merrill Lynch has an opportunity for a Quantitative Financial Analyst within our Global Risk Analytics (GRA) function. Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT) are sub-lines of business within Global Risk Management (GRM). Collectively, they are responsible for developing a consistent and coherent set of models, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA and EIT partner with the Lines of Business and Enterprise functions to ensure the capabilities it builds address both internal and regulatory requirements, and are responsive to the changing nature of portfolios, economic conditions, and emerging risks. In executing its activities, GRA and EIT drive innovation, process improvement and automation.

Overview of Consumer Model Development

The Consumer Model Development & Operations (CMDO) team is part of Global Risk Analytics. It provides quantitative solutions to enable effective risk and capital management across the Retail and Global Wealth & Investments Management (GWIM) lines of business. The team places strong emphasis on delivering world class quantitative solutions for Front Line Unit (FLU) model owners and stakeholders through a disciplined and iterative development process. The team has responsibilities across a number of areas:

• Quantitative Modeling – Develop and maintain risk and capital Models and Model Systems across Retail and GWIM product lines. Models and Model Systems provide insight into many risk areas, including loan default, exposure at default (EAD), loss given default (LGD), delinquency, prepayment, balances, pricing, risk appetite, revenues and cash flows.

• Quantitative Solutions Engineering – Architect, implement, maintain, improve and integrate quantitative solutions on strategic GRA platforms. Outputs include GRA libraries that perform consumer risk model calculations, analytical tools, processes and documentation. Partner in defining, adopting, and executing GRA’s technical strategy.

• Risk and Capital Management Capabilities – Build best in class quantitative solutions that enable the Retail and GWIM lines of business to effectively manage risk and capital, through the application of the disciplined BAU development process that includes extensive interaction with the FLU model owners and stakeholders throughout the quantitative lifecycle.

• Infrastructure – Partner in driving forward the infrastructure to support the goals of GRA through code efficiencies, and expansion of quantitative capabilities to better leverage infrastructure and computational resources.

• Documentation – Deliver concise, quantitative documentation to inform stakeholders, meet policy requirements, and enable successful engagement in regulatory exams (e.g., CCAR, CECL) via automated, modularized, and standardized documentation and presentations.

The Quantitative Finance Analyst will interact with a wide variety of stakeholders including risk managers, model developers, operations, technology, finance, and capital.
The main responsibilities will involve:

• Software development: implement, maintain, improve and integrate quantitative solutions on strategic GRA platforms. Development takes place almost entirely in Python, with some C++ for high performance components.

• Maintain code quality through best practices, unit testing and code quality automation.

• Understand the whole product, its modules, and the interrelationship between them, while being an expert in the assigned component or module.

• Possess advanced domain knowledge and show great customer focus. Leverage skills in methodologies and build, release, and deployment processes.

• Partner in defining, adopting, and executing GRA’s technical strategy.

• Identify and apply new software development techniques to support enhanced granularity of risk management capabilities. Employ elevated intellectual curiosity and an acute sense of innovation.

• Elevated intellectual curiosity with acute sense of innovation to identify and apply new statistical and econometric techniques to support enhanced granularity of risk management capabilities

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

Minimum Education Requirement:Master’s degree in related field or equivalent work experience

Required Qualifications:Successful candidates will have a minimum 5 years relevant experience and will possess the following skills:

• Strong Python software development skills

• Familiar with software design principles: separation of concerns, single responsibility, DRY, etc.

• Understanding of algorithms and data structures

• Experience with Linux operating system and command line tools

• Experience with version control systems, i.e., Git

• Knowledge of SQL

• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences

• 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

• Experience implementing models into various production environments

• Demonstrated leadership skills; Ability to exert broad influence among peers

• Strategic thinker that can understand complex business challenges and potential solutions

• Sees the broader picture and is able to identify new methods for doing things

• Ability to work in a large, complex organization, and influence various stakeholders and partners

• Ability to work in a highly controlled and audited environment

• Exceptional programming skills in high performance python

• Exceptional Terabyte-scale Spark programming and optimization

Desired Qualifications:The ideal candidate will possess the following skills and experience:

• GRA Core Platform (GCP) experience

• Familiar with systems architecture concepts: service based, layered, microservices, scalability patterns

• Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow

• Experience creating, optimizing, and debugging software solutions deployed into distributed computing environments (experience with Spark is a plus)

• Familiar with use of vectorization and data locality concepts to optimize software efficiency

• Experience with high performance Python libraries, i.e., Numpy, Numba, Cython

• Experience with LaTeX

• Familiarity with SDLC tools: unit testing libraries, Jira, Jenkins

• Consumer Financial Product Industry experience

Skills:

• Critical Thinking

• Quantitative Development

• Risk Analytics

• Risk Modeling

• Technical Documentation

• Adaptability

• Collaboration

• Problem Solving

• Risk Management

• Test Engineering

• Data Modeling

• Data and Trend Analysis

• Process Performance Measurement

• Research

• Written Communications

Job Description:

Job Description:

Quantitative engineers in Global Risk are responsible for designing and implementing common, reusable, and scalable software components. These components enable GRM’s data and analytical capabilities. These components can be domain independent (e.g., generic data quality tools over trillions of rows of data) or domain specific (e.g., classification models for surveillance or testing framework for Global Markets processes). Quantitative engineers work with modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics. Quantitative engineers have a combination of software engineering, big data, and modeling skills and the ability to work across the entire spectrum of a big data stack – from data to logic to model to UI to UX.

Responsibilities:

• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements

• Understanding financial data: schemas, flow, size, data issues, data controls, etc.

• Building performant big data pipelines

• Use programming skills and knowledge of software development lifecycle principles to deliver high quality code for model and testing processes

• Collaborate with key stakeholders across the Bank to understand modeling and testing business processes and requirements

• Think outside the box of current industry standards to develop innovative approaches

• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks

• Source and evaluate data required for modeling and testing

• Design and develop and implement models and tests

• Produce clear, concise and repeatable technical documentation models and testsfor internal and regulatory purposes

Candidates should meet all or a subset of the following technical skills:-

• Software engineering: modular code, software lifecycle processes, unit testing, regression testing

• Big data: distributed computing paradigms (e.g., mapreduce, dataframes, etc), optimizing distributed software

• Modeling / quantitative: basic modeling techniques (regression, classification, clustering, etc)

Minimum Education Requirement:

• Bachelor’s degree in Computer Science, a closely related field, or a degree from a program where software engineering was a key focus or equivalent work experience

Qualifications:

• At least 2 years of relevant experience in software engineering in Quantitative Finance or other industries

• Strong Programming skills (e.g., Python) and solid understanding of Software Development Life cycle principles

Candidates should have at least one of these following skills and preferably have at least two of these skills:-

• Strong analytical and problem-solving skills

• Experience applying quantitative methods such as modelling, data analytics, machine learning, and statistics to develop business solutions

• Experience with large scale data sets with structured or unstructured data

• Experience in building user facing applications over large amounts of data using technologies like React, Angular, JavaScript etc.

• Experience implementing process improvements and automation

Skills:

• Critical Thinking

• Quantitative Development

• Risk Analytics

• Risk Modeling

• Technical Documentation

• Adaptability

• Collaboration

• Problem Solving

• Risk Management

• Test Engineering

• Data Modeling

• Data and Trend Analysis

• Process Performance Measurement

• Research

• Written Communications

Job Description:

Job Description:

Quantitative Engineer Analyst is the entry level role to becoming a Quantitative Engineer. Quantitative engineers in Global Risk are responsible for designing and implementing common, reusable, and scalable software components. These components enable GRM’s data and analytical capabilities. These components can be domain independent (e.g., generic data quality tools over trillions of rows of data) or domain specific (e.g., classification models for surveillance or testing framework for Global Markets processes). Quantitative engineers work with modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics. Quantitative engineers have a combination of software engineering, big data, and modeling skills and the ability to work across the entire spectrum of a big data stack – from data to logic to model to UI to UX.

set of models, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA and EIT partner with the Lines of Business and Enterprise functions to ensure the capabilities it builds address both internal and regulatory requirements, and are responsive to the changing nature of portfolios, economic conditions, and emerging risks. In executing its activities, GRA and EIT drive innovation, process improvement and automation.

Job Responsibilities:

• Understanding financial data: schemas, flow, size, data issues, data controls, etc.

• Building performant big data pipelines

• Use programming skills and knowledge of software development lifecycle principles to deliver high quality code for model and testing processes

• Collaborate with key stakeholders across the Bank to understand modeling and testing business processes and requirements

• Think outside the box of current industry standards to develop innovative approaches

• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks

• Source and evaluate data required for modeling and testing

• Design and develop and implement models and tests

• Produce clear, concise and repeatable technical documentation on models and testsfor internal and regulatory purposes

Skills:

• High level of intellectual curiosity

• Feel ownership and accountability for delivering high quality work, able to prioritize effectively, adapt, and meet strict deadlines

• Strong written, verbal, presentation creation and delivery skills

• Well organized, and has attention to detail

This job is responsible for conducting quantitative analytics and complex modeling projects for specific business units or risk types. Key responsibilities include leading the implementation and development of new models, analytic processes, or system approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations may include the ability to influence strategic direction, as well as develop tactical plans.

Responsibilities:

• Turn modeler code into a highly scalable big-data production application

• Identify continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation

• Lead and provide methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk

• Work closely with model stakeholders and senior management with regard to communication of submission and validation outcomes

• Perform analysis on large datasets and interpret results using both qualitative and quantitative approaches

Minimum Education Requirement:Master’s degree in related field or equivalent work experience

Required Skills and Experience:Successful candidates will have a minimum 10 years relevant experience and will possess the following skills:

• Advanced big data software development skills in both python and spark

• Deep expertise in Loss and Risk Forecasting Automation: odds calculations, cash flow calculations, model monitoring, back testing, reporting, etc.

• Sees the broader picture and can identify new methods for doing things

• Experience with Linux operating system and command line tools

• Familiar with software design principles: separation of concerns, single responsibility, DRY, etc.

• Understanding of algorithms and data structures

• Experience with version control systems, i.e., Git

• Knowledge of SQL

• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences

• 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

• Experience implementing models into various production environments

• Demonstrated leadership skills; Ability to exert broad influence among peers

• Strategic thinker that can understand complex business challenges and potential solutions

• Ability to work in a large, complex organization, and influence various stakeholders and partners

• Ability to work in a highly controlled and audited environment

Desired Skills and Experience:The ideal candidate will possess the following skills and experience:

• GRA Core Platform (GCP) experience

• Familiar with systems architecture concepts: service based, layered, microservices, scalability patterns

• Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow

• Experience creating, optimizing, and debugging software solutions deployed into distributed computing environments (experience with Spark is a plus)

• Familiar with use of vectorization and data locality concepts to optimize software efficiency

• Experience with high performance Python libraries, i.e., Numpy, Numba, Cython

• Experience with LaTeX

• Familiarity with SDLC tools: unit testing libraries, Jira, Jenkins

• Consumer Financial Product Industry experience

Skills:

• Critical Thinking

• Quantitative Development

• Risk Analytics

• Risk Modeling

• Technical Documentation

• Adaptability

• Collaboration

• Problem Solving

• Risk Management

• Test Engineering

• Data Modeling

• Data and Trend Analysis

• Process Performance Measurement

• Research

• Written Communications

Job Description:

Job Description:

This job is responsible for defining and leading the engineering approach for complex features to deliver significant business outcomes. Key responsibilities of the job include delivering complex features and technology, enabling development efficiencies, providing technical thought leadership based on conducting multiple software implementations, and applying both depth and breadth in several technical competencies. Additionally, this job is accountable for end-to-end solution design and delivery.

Responsibilities:

• Ensures that the design and engineering approach for complex features are consistent with the larger portfolio solution

• Define the technology tool stack for the solution and evaluate and adapt new testing tool/framework/practices for team(s)

• Enables team(s)/applications with Continuous Integration/Continuous Development (CI/CD) capabilities and engages with other technical stakeholders pertaining to efficient functioning of CI-CD pipeline

• Guides and influences team(s) on design and best practices for high code performance –e.g. pairing, code reviews

• Provides end-to-end delivery of complex features, including automation, for either a single team or multiple teams, at the program level

• Conducts research, design prototyping and other exploration activities such as evaluating new toolsets and components for release management, CI/CD, and features

• Works with stakeholders to establish high-level solution needs and with architects for technical requirements

Required Qualifications:

• Possess 10+ years of experience as an architect, development lead in a complex financial industry data environment.

• Extensive experience working in a complex workflow automation and excellent understanding of Banking.

• Strong proven experience in workflow / Case Management solutions using Pega.

• Strong proven experience in handling medium to large size Pega Application development projects by providing solution design & architecture.

• Owns end to end solution architecture and design for a set of applications within the portfolio

• Extensive hands-on architecture, design and development experience with large-scale application & technology solutions with multiple stakeholders. Reusable framework design/development experience is a plus.

• Extensive hands-on architecture, design and development of micro services general patterns and practices.

• Demonstrate strong leadership, communication, analytical and organizational skills.

• Ability to effectively manage day-to-day interactions and relationships with a diverse group of colleagues.

• Put people at ease when necessary and instill a high degree of trust quickly and genuinely.

• Effectively manage resource allocations to match the budget and keep track of it

• Effectively lead teams and inspire others to achieve goals through innovation, quality and excellence

• Contribute to improve process efficiencies/ Agile enablement etc. for the benefit of the organization

• Manage/track team compositions and maintain balance within Agile teams in regard to resource attrition (Dev)

Skills:

• Automation

• Influence

• Result Orientation

• Stakeholder Management

• Technical Strategy Development

• Application Development

• Architecture

• Business Acumen

• Risk Management

• Solution Design

• Agile Practices

• Analytical Thinking

• Collaboration

• Data Management

• Solution Delivery Process

: Bachelor’s degree or equivalent work experience.

Job Description:

Job Description:

This job is responsible for defining and leading the engineering approach for complex features to deliver significant business outcomes. Key responsibilities of the job include delivering complex features and technology, enabling development efficiencies, providing technical thought leadership based on conducting multiple software implementations, and applying both depth and breadth in several technical competencies. Additionally, this job is accountable for end-to-end solution design and delivery.

Responsibilities:

• Ensures that the design and engineering approach for complex features are consistent with the larger portfolio solution

• Define the technology tool stack for the solution and evaluate and adapt new testing tool/framework/practices for team(s)

• Enables team(s)/applications with Continuous Integration/Continuous Development (CI/CD) capabilities and engages with other technical stakeholders pertaining to efficient functioning of CI-CD pipeline

• Guides and influences team(s) on design and best practices for high code performance –e.g. pairing, code reviews

• Provides end-to-end delivery of complex features, including automation, for either a single team or multiple teams, at the program level

• Conducts research, design prototyping and other exploration activities such as evaluating new toolsets and components for release management, CI/CD, and features

• Works with stakeholders to establish high-level solution needs and with architects for technical requirements

Required Qualifications:

• Possess 10+ years of experience as an architect, development lead in a complex financial industry data environment.

• Extensive experience working in a complex workflow automation and excellent understanding of Banking.

• Strong proven experience in workflow / Case Management solutions using Pega.

• Strong proven experience in handling medium to large size Pega Application development projects by providing solution design & architecture.

• Owns end to end solution architecture and design for a set of applications within the portfolio

• Extensive hands-on architecture, design and development experience with large-scale application & technology solutions with multiple stakeholders. Reusable framework design/development experience is a plus.

• Extensive hands-on architecture, design and development of micro services general patterns and practices.

• Demonstrate strong leadership, communication, analytical and organizational skills.

• Ability to effectively manage day-to-day interactions and relationships with a diverse group of colleagues.

• Put people at ease when necessary and instill a high degree of trust quickly and genuinely.

• Effectively manage resource allocations to match the budget and keep track of it

• Effectively lead teams and inspire others to achieve goals through innovation, quality and excellence

• Contribute to improve process efficiencies/ Agile enablement etc. for the benefit of the organization

• Manage/track team compositions and maintain balance within Agile teams in regard to resource attrition (Dev)

Skills:

• Automation

• Influence

• Result Orientation

• Stakeholder Management

• Technical Strategy Development

• Application Development

• Architecture

• Business Acumen

• Risk Management

• Solution Design

• Agile Practices

• Analytical Thinking

• Collaboration

• Data Management

• Solution Delivery Process

: Bachelor’s degree or equivalent work experience.