Sr. Quantitative Finance Analyst

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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

Bank of America’s Global Risk Analytics (GRA) organization has a high impact opportunity for a Senior Quantitative Financial Analyst within its Consumer Loss Forecasting (CLF) team.
GRA is a quantitative organization which delivers models, tools, and analysis needed to effectively manage risk and capital. The CLF team provides insights via credit loss forecasts and related portfolio, model and forecast analytics for Bank’s $500 billion consumer loan portfolio – which includes Mortgage, Credit Card, Auto loan, and Consumer Banking Overdraft products. This position will primarily focus on the Consumer Credit Card product and portfolio. 

Forecast Administration plays a critical role in the Bank’s allowance and financial planning, enterprise stress testing, and overall risk management activities. It requires combining knowledge of operational management, impacts of product and financial strategies, with analytical skills to enhance risk assessment and loss forecasting capabilities, adding insights to help improve business decision-making.

The Senior Quantitative Financial Analyst interacts with a wide variety of stakeholders including other loss forecast associates, model operations, model developers, Allowance, Finance, Enterprise Stress Testing, Risk and the Front Line Unit. The Analyst should be able to effectively conduct sophisticated analysis and communicate results of such analysis to stakeholders. 

Forecast Administration Team Responsibilities:
Each of the following responsibilities require advanced analytical and quantitative capabilities along with strong written and verbal communication skills. Being able to influence resources from within the team or across other teams, and the ability to quickly identify core implications and connections within complex issues is needed in this role.

• Create crisp executive-level analytic content for stakeholders. This includes creating commentary to effectively explain trends, analyze loss projections, portfolio credit quality, and ensure loss forecast reasonability.

• Utilizing cards business knowledge to assess loss model historical back-testing to facilitate recommended forecast adjustments and provide feedback to Model Development. This includes presenting adjustment rationale to stakeholders, obtaining buy-in from partners, and collaborating with model development partners to address existing or emerging model limitations.

• Drive analytics pipeline covering strategy and environmental impacts, as well as consumer financial health on portfolio trends vs. model performance.

• Collaborate across teams to ensure portfolio and business decisions impacts are accounted for in the forecast.

Required Skills:

• 8+ years of Consumer Unsecured analytics experience preferably data analytics, or quantitative research, forecast methods, credit acquisition or existing account management strategy experience, Finance or Collections data analytics, risk management, or quantitative research

• Experience in Risk, Credit, Product Management, Collections or Financial Operations with demonstrated track record of generating and communicating insights which improve performance and understanding

• Navigating and building expertise in new/unfamiliar data sources (internal or external) to correctly interpret data and extract information needed for analysis

• Designing analytical framework / experiment to effectively answer business questions

• Storyteller with demonstrated ability to deliver data insights to business in succinct and digestible manner through strong intuition on linkage between data observations and business significance and effective use of data visualization techniques

• Highly proficient at SQL, demonstrated ability to transform data into analysis ready format

• Attention to detail coupled with ability to simplify the complex

• Demonstrated ability to independently drive, organize and work collaboratively across multiple teams and functions

• Flexibility to work independently with little supervision in a complex team environment

• Proficiency with Tableau, MS Word/Excel/PowerPoint

• Previous demonstrated strong leadership or project management experience

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

Shift:

1st shift (United States of America)

Hours Per Week: 

40