Officer, Quantitative Finance Analyst

About the position At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates' physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Responsibilities

• Apply quantitative models and techniques in order to address and resolve concrete financial problems.
• Utilize advanced quantitative techniques and tools, such as, statistical analysis and linear regressions, as needed.
• Develop emerging risk assessments, analyze counterparty credit risk scenarios and model key risk factors.
• Conduct research and analysis to provide a micro view of risk management in a particular counterparty or country and a macro view of risk exposures for the bank.
• Assess market trends and provide quantitative data for internal stakeholders and regulators.
• Apply quantitative knowledge to specific financial challenges and regulatory projects.
• Prepare developmental evidence and document to support internal requests and external regulatory exams.
• Perform in-depth analysis on the bank's risk model results using various quantitative tools including back testing, benchmarking, and sensitivity analysis.
• Perform counterparty exposure management techniques, such as potential future exposure, stress testing, and wrong way risk.
• Develop product-specific analytics to measure and monitor risk calculations.
• Coordinate efforts across teams and lines of business to enhance existing credit and market risk analysis tools.
• Perform quantitative modeling by utilizing advanced quantitative techniques and tools of statistical analysis, econometrics, predictive modeling, linear regressions, and Machine Learning.
• Analyze and evaluate large and complex economic and financial datasets with analytical tools of Python, SQL, and R.
• Utilize Python, PySpark, and SQL to conduct data analysis, estimate model coefficients, run simulations, and aggregate the model results to generate comprehensive model outputs and benchmarks.
• Leverage data analytics and visualization tools including Tableau, Alteryx, R, and Jupyter Notebook to build easy-access analytical capabilities and insightful reporting for the management.
• Utilize Latex to produce technical reports of publication quality with academic rigor and comprehensive risk coverage to support internal reviews and assess with stakeholders.
• Remote work may be permitted within a commutable distance from the worksite.

Requirements

• Master's degree or equivalent in Business Analytics, Mathematical Economics, Technology (any), Engineering, Statistics or related: and
• 1 year of experience in the job offered or a related Quantitative occupation.
• Must include 1 year of experience in:
• Performing quantitative modeling by utilizing advanced quantitative techniques and tools of statistical analysis, econometrics, predictive modeling, linear regressions, and Machine Learning;
• Analyzing and evaluating large and complex economic and financial datasets with analytical tools of Python, SQL, and R;
• Utilizing Python, PySpark, and SQL to conduct data analysis, estimate model coefficients, run simulations, and aggregate the model results to generate comprehensive model outputs and benchmarks;
• Leveraging data analytics and visualization tools including Tableau, Alteryx, R, and Jupyter Notebook to build easy-access analytical capabilities and insightful reporting for the management; and,
• Utilizing Latex to produce technical reports of publication quality with academic rigor and comprehensive risk coverage to support internal reviews and assess with stakeholders.

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