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Senior Quantitative Finance Analyst

1 month ago

Atlanta, Georgia, United States Bank of America Full time
Job Title: Senior Quantitative Finance Analyst

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.

We are seeking a highly skilled Senior Quantitative Finance Analyst to join our team. As a key member of our risk management team, you will be responsible for conducting quantitative analytics and complex modeling projects for specific business units or risk types.

Key Responsibilities:
  • Perform end-to-end market risk stress testing, including scenario design, implementation, results consolidation, internal and external reporting, and analysis of stress scenario results to better understand key drivers.
  • Lead the planning related to setting quantitative work priorities in line with the bank's overall strategy and prioritization.
  • Identify 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.
  • Maintain and provide oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite.
  • Lead and provide 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.
  • Work closely with model stakeholders and senior management with regard to communication of submission and validation outcomes.
  • Perform statistical analysis on large datasets and interpret results using both qualitative and quantitative approaches.
Requirements:
  • Masters degree in a related field or equivalent work experience.
  • Advanced quantitative degree (PhD or MS in statistics, math, physics, computer science, etc.) with 5+ years of hands-on model development or validation experience in fraud detection or related financial crime areas.
  • Solid grasp of traditional statistical modeling techniques (e.g. Logistic regression) plus advanced AI/ML techniques (Gradient Boosting, Neural Networks, Random Forest, etc.).
  • Expertise in model evaluation techniques such as rank ordering, ROC curve, confusion matrix, KS, cross-validation, feature importance, SHAP values, etc.
  • Proficiency in Python, SAS, R, LaTEX, etc.
  • Familiarity with regulatory requirements and guidelines related to risk model validation.
  • Excellent communication skills; excellent writing skills.
  • Excellent analytical thinking, practical problem-solving skills, and ability to work well with people at all levels.