Sr Quantitative Finance Analyst

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities, and shareholders every day. Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being a diverse and inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing, and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

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:

• 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
• 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

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

Line of Business Job Description:

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 Teams are responsible for model inventory management, model development and enhancement, model tuning and optimization, model risk management, and model analysis and incident management

Overview of Role:
Responsible for leading the development of AML transaction monitoring or Customer Due Diligence (CDD) modeling independently.
 

Responsibilities include, but not limited to:

• Support AML and CDD 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/CDD interim compensating control initiatives
• Conduct and support below-the-threshold sampling
• 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

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 skill

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

Education:

• Graduate degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)
• 3+ years (2+ years with a PhD) of experience in model development, statistical work, data analytics or quantitative research

Shift:

Hours Per Week: