Senior Quantitative Finance Analyst

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Team Overview:

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. Modeling and Analytics Team are responsible for model inventory management, model development and enhancement, model tuning and optimization, model risk management, and model analysis and incident management:
1) US AML Modeling and Analytics is responsible for development and maintenance of all US AML Feeder models as per acceptable model risk practices and defined performance parameters to meet firm’s AML Risk Coverage, while maintaining operational viability.
2) Non-US AML Modeling & Analytics is responsible for development and maintenance of Non-US AML Feeder models to address the regional regulatory guidelines while meeting the bank’s AML Risk Coverage. Automates suspicious activity monitoring while optimizing the effectiveness and the efficiencies of our models for the detection of potential threats.
3) Case Generation Modeling & Analytics is responsible for the EP model which consolidates and risk ranks alerts generated from US and Non-US AML detection models and promotes suspicious activity as cases for investigation.
4) Economic Sanction and Screening Modeling & Analytics is responsible for models that detect and prohibit transactions made by individuals or entities that are listed on sanctions watch lists.
5) Ongoing Monitoring Review, Management Information, Analysis and Below-the-Line/Threshold (BTL/BTT) Testing 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. The team is also responsible for management information design and implementation, investigations forecasting, and BTL/BTT framework design and oversight.
6) Engineering, Data & Analytics is responsible for model development and testing platforms, model production and delivery, model data framework, key business elements, and specialized and complex analytics.
7) Research and Development is responsible for future thinking concepts, innovation coordination, tools and technique assessment, artificial intelligence oversight, and vendor assessment oversight.
8) 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.
9) Business Management & Control is responsible for Strategy, Governance Oversight and Control, Resource Management, Process Excellence, Issue Management and COO function.

Role Overview:

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

• Responsible for leading the development of Case Generation AML model development.

• Support AML Modeling with Ad-hoc Analytics, Distribution Analysis, Sensitivity Analysis

• Support GFC with additional data analytics for drafting Business Requirement Document

• Lead analytical support for various AML interim compensating control initiatives

• Conduct and support below-the-threshold sampling

Main Responsibilities :

• 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 and/or Experience Requirement:

• Master’s degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics) or 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

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. R, Python, SAS, SQL, R or other languages

• Strong analytical and problem-solving skills

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

• Strong technical writing, communication and presentation skills and ability to effectively communicate quantitative topics with non-technical audiences

• Effective at prioritization/time and project management

• Broad understanding of financial products

• 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

• Demonstrated ability to drive action and sustain momentum to achieve results

• 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

Shift:

1st shift (United States of America)

Hours Per Week:

40