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Job Description:
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

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

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

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.
One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We're devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.
Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization. Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Overview of GRA:
Bank of America Merrill Lynch has an opportunity for a Quantitative Finance Analyst 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 Team:
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 seven sub-teams:
• Financial Crime Model Development responsible for development and maintenance of all AML Feeder models as per acceptable model risk practices and defined performance parameters to meet firm's AML Risk Coverage, while maintaining operational viability.
• Ongoing Monitoring Review is responsible for periodically substantiating the ongoing fitness of financial crime models in accordance with a model's approved Ongoing Monitoring Plan ("OMP"). Ongoing Model Monitoring Reports ("OMRs") assess environmental changes, model limitations, assumptions, process verification and outcomes analysis for each model. OMRs summarize trends in key metrics and provide critical analysis of model performance with respect to metric thresholds; identify threshold breaches and document remediation plans. In addition, the ongoing monitoring process includes the inline monitoring activities performed between reporting cycles, the results of those activities, and any escalations during the period.
• Economic Sanctions responsible for development and maintenance for Economic Sanction models. Provides capabilities to better solve data analytical problems in risk management, identify new business insights and opportunities from data, and enhance the firm's risk management tools.
• Engineering, Data & Analytics, Model Implementation, Event Processor Model Development is responsible for designing end-to-end data and process flows for model development, testing, and execution, including architecture setup; delivering model code to technology teams for production releases; developing models (Event Processor), analytics (Event Processor Performance Analysis, Transaction Monitoring Analysis) and tools (FinCAP) to enhance risk metrics and facilitate what-if/explain scenario analysis.
• Program Management & Regulatory is responsible for overseeing cross-functional initiatives and providing project management support to deliver timely execution of GFCMA's book of work, strategic initiatives, and critical activities in support of regulatory and audit deliverables.
• Business Management & Control is responsible for Strategy, Governance Oversight and Control, Resource Management, Process Excellence, Issue Management and COO function
• Administration provides administrative and organizational support to the GFCMA executive and leadership team.

As a Quantitative Finance Analyst on the Global Financial Crimes Modeling and Analytics team, your main responsibilities will involve:
• 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.
• 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

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

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

Qualifications:
• 2+ years of experience in model development, statistical work, data analytics or quantitative research, or PhD
• Effectively creates a compelling story using data; Able to make recommendations and articulate conclusions supported by data
• Strong Programming skills e.g. R, Python, SAS, SQL, R or other languages

Desired Skills and Experience:
• Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
• Knowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniques
• Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis
• Experience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutions
• Experience with data analytics tools (e.g., Alteryx, Tableau)
• 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
• Sees the broader picture and is able to identify new methods for doing things
• Experience with LaTeX

Shift:
1st shift (United States of America)

Hours Per Week:
40