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!

Overview of Global Risk Analytics

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 the Team

Treasury Analytics Quantitative Team is part of Global Risk Analytics (GRA). The team is staffed by analysts who apply an extensive set of quantitative methods for effective asset liability management.  Methods include, but are not limited to, econometric and statistical forecasting models for mortgages, loans and deposit products across the bank’s balance sheet. The group provides quantitative models and analytics support for Interest Rate Risk / Liquidity Risk measurement and management. This role provides an opportunity to develop models for deployment on advanced analytical platforms with significantly parallelized architecture for data analysis / computation and model execution capabilities, to satisfy computational needs within Corporate Treasury.

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:

• 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.

• Research and apply quantitative techniques in financial mathematics, applied mathematics and statistics to enhance forecasting for risk measurement and asset liability management

• Design and build econometric behavioral models pricing and valuation tools, for mortgage backet securities, loans and a variety of deposit products on the bank’s balance sheet

• Responsible for technical documentation, model implementation, data management, model analysis, model performance monitoring. Contribute to process improvement and automation across all of these activities

• 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

Required Qualifications:

• Working knowledge of risk or pricing models for fixed income or commodity products

• Understanding of regulatory capital and risk management framework and stress testing requirement

• Solid working experience in a related field (Market Risk, Middle Office)

• Expertise in Statistical Programming Software such as R, and experience in data analysis

• Proven programming skills (Python, C++, SQL, or equivalent object-oriented programming) to write reusable and testable code to develop tools and improve process efficiency for reporting and calculation automation

• Pro-active behavior with capacity to seize initiative

• Good written and oral communication, interpersonal and organizational skills and ability to build and maintain relationships with personnel across areas and regions

• Ability to multitask with excellent time management skills

• Possess excellent quantitative/analytic skills and a broad knowledge of financial markets and products

• Strong skills/intuition in Economics and Finance

• Ability to work individually and with the group on complex problem solving; analytical skills, critical thinking with a strong desire to learn

• Strong attention to detail, excellent communication skills and ability to work well in a cooperative, time-sensitive, market-driven environment

• Ability to manage multiple priorities with minimal supervision

Desired Qualifications:

• Strong academic background in econometrics or statistics (M.S. or PhD in a STEM/Economics field)

• Experience with computational and simulation methods

• Places value on process automation with an eye for reproducibility of results

• Experience working with Unix/Linux environment

• Past experience in Interbank Offering Rate (IBOR) transition / Fundamental Review of the Trading Book (FRTB) is a plus

Minimum Education Requirement:

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

Shift:

1st shift (United States of America)

Hours Per Week: 

40