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 has an opportunity for a Senior Quantitative Finance Analyst within the Alternative Modelling Group (AMG), a Global Risk Analytics (GRA) team. Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM). The GRA team provides quantitative capabilities supporting global risk management and capital management and develops a consistent set of risk and capital models and analytical tools that support decision making across the bank. As part of GRA - Alternative Modelling Group (AMG) builds alternative models, using innovative methods, which challenge and benchmark risk and capital champion models across the enterprise; and has a vision to challenge what is possible across Risk and Capital Modelling. The role will involve re-designing, optimising, and leading the development, implementation and deployment of the next generation of Risk and Capital models to improve the bank’s risk management capability. This is a challenging and intellectually stimulating role, across a dynamic and innovative risk and capital modelling portfolio that spans the Enterprise. We are looking for experienced technically minded problem solvers with proven leadership credentials and the desire to work across functional areas to drive the design framework, model development, implementation, and deployment of next generation risk and capital models; including champion and challenger; able to leverage a wealth of experience in the pursuit of modelling excellence.

Responsibilities:

• Provide leadership and technical acumen and experience in the design, development, implementation and deployment of new models, analytic processes or systems approaches.

• Critical to the role is to be able to provide current industry standards to develop innovative approaches to modelling problems.

• Collaborate with stakeholders across the company to collect requirements and then develop and build modelling and technical solutions to meet them; and effectively communicate those solutions to stakeholders.

• Provide insight and thought leadership into the implementation of new models, analytic processes or systems approaches.

• Promote the adoption of industry best practice for model development, implementation and monitoring.

• Collaborate with stakeholders across the firm to identify opportunities to improve existing models/processes.

• Produce clear and coherent technical documentation for internal and regulatory purposes.

• Be able to effectively govern models and processes to ensure we meet the highest levels of regulatory expectation.

• Take ownership to deliver results and meet critical deadlines.

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

Required Qualifications:

• Highly numerical degree (Masters required and PhD level desirable) in Statistics, Financial Mathematics, Applied Mathematics, Economics, Physics or Engineering

• Several years of relevant work experience or equivalent educational training

• Technical skills: Statistics, Probability Theory, Econometrics, Financial Mathematics

• Experience developing and implementing large quantitative models, managing large data sets.

• Proven leadership abilities, working across organizational lines.

• Strong programming skills; SQL, Python, VBA, Latex

• Strong technical writing and clear verbal communication skills

• Experience of, and ability to work under pressure and deliver to tight deadlines.

• Ability to work independently, multitask and properly prioritize multiple projects.

• Curiosity and willingness to develop and work on new ways of modelling.

• Capable of providing leadership to junior team members

• Organized, practical and execution focused with some project management experience.

Desired Qualifications:

• Experience in financial risk modelling, Capital modelling, loss forecasting etc.

• Knowledge of regulatory guidelines including CCAR, CECL, DFAST, ICAAP.

• Good stakeholder engagement skills with an ability to collaborate with colleagues in other functions (business, risk and model validation)

• Self-motivated and intellectually curious about both the role, supporting technologies and the wider bank.

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

Shift:

1st shift (United States of America)

Hours Per Week:

40