Quantitative Finance Analyst - Consumer Loss Forecasting (CLF) Team
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Bank of America
What would you like the power to do? At Bank of America, our purpose is to help make financial lives better through the power of every connection.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. 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 Global Risk Analytics
Bank of America Merrill Lynch has an opportunity for a Quantitative Finance Analyst (B5) 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 these activities.
Overview of the Role
The Quantitative Financial Analyst interacts with a wide variety of stakeholders including risk managers, model developers, operations, technology, finance, and capital. The Analyst will identify, lead, and organize strategic change efforts across the team including new model deployment and analytical capability development.
As a Quantitative Finance Analyst within Global Risk Analytics, your main responsibilities will involve:
• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements
• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks
• Understanding and executing activities that form the end-to-end model development and use life cycle
• Identifying requirements from the teams which improve the group’s ability to generate insights and understanding of portfolio risk, model accuracy, and forecast reasonability
• Clearly documenting and effectively communicating quantitative methods as part of ongoing engagement with key stakeholders, including the lines of business, risk managers, model validation, technology
Position Overview
The Consumer Loss Forecasting (CLF) team is part of Global Risk Analytics (GRA). CLF provides analytical insights and loss forecasts, enabling improved Credit Risk management. This collective output is utilized for allowance setting, financial planning, Comprehensive Capital Analysis & Review (CCAR) submission, and other business decision-making. This position will primarily focus on the Small Business Card (SBC) portfolio from a loss forecast administration, analytics, enablement and control standpoint. In order to deliver risk management insights, the position will require the following:
• Conduct research and analysis to improve understanding and assessment of loan portfolios, models used and forecast results
• Develop, maintains, and execute select models, quantitative methods, assumptions utilized in loss forecasting; and associated tools and reports
• Manages related infrastructure and processes that enable forecasts and analytics together with Operations
• Partners with Consumer lines of business, and front line Risk, Allowance, and Finance teams to ensure consistency and appropriateness of the team’s various processes
The Quantitative Financial Analyst interacts with a wide variety of stakeholders including risk managers, model developers, operations, allowance, finance, enterprise stress testing and the front line unit. The Analyst should be able to effectively communicate complex trends impacting the loss projection, including economic, modeling and consumer health concepts and trends. The Analyst will identify, lead, and organize strategic change efforts across the forecasting team including forecast administration, new model deployment and analytical capability development for the SBC portfolio.
SBC Forecast Administration includes:
• Identifying needs and requirements for each loss submission cycle, inclusive of economic scenarios, forecast attributions and sensitivities
• Assessing loss model historical back-testing by component to facilitate recommended forecast adjustments; this includes presenting rationale to stakeholders and obtaining buy-in from partners
• Create and lead executive-level forecast and analytics content for Loan Loss Working Group meeting
Analytical capability development includes:
• Identifying needs and requirements from the CLF team which improve the group’s ability to generate insights and understanding of portfolio risk, model accuracy, and forecast reasonability
• Identifying new topics for analytical inquiry
• Organizing across teams to ensure need fulfillment
There is also the opportunity to directly conduct analysis and develop new insights. Each of these responsibilities require strong written and verbal communication skills, influencing resources from other teams, and the ability to identify core implications and connections within complex issues.
Required and Desired Candidate Qualifications
Required Skills
• Bachelor’s degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)
• 2+ years of experience in model development, statistical work, data analytics or quantitative research
• Experience in Risk, Credit, Collections or Financial Operations with demonstrated track record of generating and communicating insights which improve performance and understanding
• Strong business and financial acumen
• Attention to detail coupled with ability to simplify the complex
• Experience in data science and analysis, with excellent analytical skills
• Strategic thinker that can understand complex business challenges and potential solutions
• Demonstrated ability to organize and work collaboratively across multiple teams and functions
• Strong written/oral communication skills, with the ability to adjust to both technical and executive audiences
• Flexibility to work both independently with little supervision and in a complex team environment
• Proficiency with Tableau, MS Excel, and PowerPoint
Desired Skills
• Consumer behavior analytics or risk modeling in a financial institution
• Programing skills (SQL, Python, R, LaTeX)
• Experience meeting with internal / external examiners and responding to questions and required actions
• Experience with DFAST / CCAR
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: Bachelor’s degree in related field or equivalent work experience
Shift:
1st shift (United States of America)Hours Per Week:
40* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Credit risk Data Analytics Data management Economics Engineering Excel Finance Mathematics ML models Model deployment Physics Python R Research SQL Statistics Tableau Testing
Perks/benefits: Career development Health care
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