Senior Quantitative Risk Analyst

2 weeks ago

New York, New York, United States Bank of America Full time
Job Overview:

At Bank of America, we are driven by a shared mission to enhance financial well-being through meaningful connections. Our commitment to Responsible Growth shapes our operations and ensures we deliver exceptional value to our clients, colleagues, communities, and shareholders every day.

We prioritize creating an inclusive and diverse workplace, recognizing that varied backgrounds and experiences enrich our organization. We invest significantly in our employees and their families, offering competitive benefits that support their overall well-being—physically, emotionally, and financially.

Bank of America values collaboration while also providing flexibility tailored to the diverse roles within our organization.

Working with us presents a remarkable opportunity to advance your career, gain valuable insights, and make a significant impact.

Position Summary:
Enterprise Model Risk Management is seeking a Senior Quantitative Risk Analyst to perform independent evaluations and assessments of a wide array of models utilizing advanced statistical methodologies, as well as artificial intelligence (AI) and machine learning (ML) techniques, specifically for models related to Operational Risk and Global Operations. The portfolio encompasses models critical to business functions, which receive ongoing attention from senior management and regulatory bodies. This role is crafted to offer both strategic insight and practical expertise in methodologies, techniques, and adherence to model risk management standards.

Key Responsibilities:

• Conducting model evaluation tasks, including independent validation/challenge, annual assessments, ongoing monitoring report evaluations, required action item reviews, and peer assessments.

• Executing governance tasks such as model identification, approval processes, and breach remediation reviews to mitigate model risk.

• Offering methodological, analytical, and technical support to effectively challenge and influence the strategic direction and tactical methodologies of these initiatives.

• Engaging and collaborating directly with relevant modeling teams and their corresponding Front Line Units; if necessary, liaising with the third line of defense (e.g., internal audit) and external regulators.

• Composing technical reports for dissemination and presentation to model developers, senior management, audit teams, and regulatory authorities.

• Serving as a leader and Subject Matter Expert (SME) to assist management in decision-making and guide junior team members.

Educational Requirements:
Master's degree in a relevant field.

Essential Qualifications & Skills:

• PhD or Master's in a quantitative discipline such as Mathematics, Physics, Finance, Engineering, Computer Science, or Statistics.

• Over 8 years of experience in quantitative research, model development, and/or model validation, including at least 3 years of experience with Operational Risk Stress Testing (CCAR) and capital models.

• Profound knowledge of financial, mathematical, and statistical theories and practices, along with a comprehensive understanding of the modeling process, performance metrics, and model risk governance. Familiarity with the additional risks associated with AI/ML models is advantageous.

• Proficiency in at least one high-level programming language such as Python or R.

• Domain expertise in banking operations, stress testing, and technology related to operations management/enablement is beneficial.

• Excellent written and verbal communication skills, with the ability to collaborate effectively. This role requires interaction with various groups within the organization, including stakeholders with non-technical backgrounds.

• Strong critical thinking abilities and the capacity to independently and proactively identify, suggest, and resolve issues.

Core Competencies:
  • 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
Work Schedule:
1st shift (United States of America)

Weekly Hours:
40

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