Quantitative Developer jobs

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:

This job is responsible for conducting quantitative analytics and complex modeling projects for specific business units or risk types. Key responsibilities include leading the 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:

• Leads the development of AML models to support business requirements and the enterprise's risk appetite collaborating with the Technology, Global Financial Crimes, and Model Risk Management teams

• Leads 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

• Maintains and provides oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite

• Leads and provides 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

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

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.

As a part of Global Risk Analytics, Global Financial Crimes Modeling and Analytics is responsible for enterprise-wide financial crime model development and implementation, ongoing performance monitoring and optimization, data usage, and research and development utilizing advanced analytical tools and systems. The Global Financial Crimes Modeling and Analytics team is made up of nine sub-teams:

7) Research and Development is responsible for future thinking concepts, innovation coordination, tools and technique assessment, artificial intelligence oversight, and vendor assessment oversight.

Overview of 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.

• 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

Qualifications:

• 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 creates a compelling story using data; Able to make recommendations and articulate conclusions supported by data

• 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 Programming skills e.g. Python, SAS, SQL, or other languages

• Strong analytical and problem-solving skills

Required Education and Work Experience:

• Master’s degree in related field or equivalent work experience

• 3+ years (2+ years with a PhD) of experience in model development, statistical work, data analytics or quantitative research

• 5+ years of leadership and/or management experience

Essential Responsibilities:

• Performs SaaS and enterprise-wide applications assignments using specialized enterprise systems knowledge and developed business expertise
• Leads enterprise-wide applications projects and/or programs within PayPal with moderate scope impacting information technology or enterprise systems functions
• Analyzes, evaluates, and makes decisions within general parameters under broad supervision
• May act as an enterprise systems resource for entry level and developing colleagues

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

Our Benefits:

Any general requests for consideration of your skills, please

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Your Career

As the Principal Product Marketing Manager, Strata Cloud Manager, you will be the expert, voice and go-to-market driver for the first AI-powered, unified solution for network security management and operations. You will work closely with product management, product marketing and other cross-functional stakeholders to define and execute the positioning, messaging and all marketing activities. You will also drive messaging and content creation for the Strata Network Security platform.

Your Impact

• Work closely with Product Management to build a shared market and product vision, and a cooperative relationship that forms the foundation of all product marketing activities
• Coach the marketing strategy and content of other Strata Cloud Manager product marketers
• Be a subject matter expert and a go-to resource for the sales and field marketing teams
• Create strong product marketing content, including datasheets, whitepapers, blogs, and presentations - you like to write and present
• Leverage an in-depth knowledge of network security to translate product capabilities into simple, compelling messages and tools that resonate with customers
• Present at internal and external events, highlighting our vision for SCM and Platform.

Your Experience

• 10+ years of product marketing experience with a strong preference for experience in Network Security
• Deep understanding of network security domain, market trends, competitive landscape and customer requirements
• Outstanding technical, verbal and written communication skills
• Comfortable with creating and delivering presentations in a range of environments, from industry conferences to customer and industry analyst briefings
• Demonstrated record of working cross-functionally to drive sales, demand generation and overall organization and business success
• Experience and innovative energy to champion successful market and competitive disruption initiatives

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $155000/YR - $252000/YR The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found .

All your information will be kept confidential according to EEO guidelines.