Quantitative Finance Analyst

Job description

Job Description: 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. One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being. Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization. Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us! As a Quantitative Finance Analyst on operational risk in the Risk Analytics team, your main responsibilities will involve: • Applying quantitative methods to develop models on operational risk that meet line of business, risk management and regulatory requirements • Maintaining and continuously enhancing models and related processes, such as model execution and ongoing monitoring, over time to respond to the changing nature of portfolios, economic conditions and emerging risks • Understanding and executing activities that form the end-to-end model development and use life cycle • Clearly documenting and effectively communicating quantitative methods as part of ongoing engagement with key stakeholders, including the lines of business, risk managers, model validation, technology Position Overview • Responsible for independently conducting quantitative analytics and modeling projects on operational risk. Responsible for developing new models, analytic processes or systems approaches on operational risk stress testing and capital estimation. Creates documentation for all activities and works with Technology staff in design of any system to run models developed. Incumbents possess excellent quantitative/analytic skills and a broad knowledge of financial markets and products. 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 Supports 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 Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite Supports the 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 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 Minimum Education Requirement: Master’s degree in related field or equivalent work experience Desired Skills: • 2+ years of experience in model development, statistical work, data analytics or quantitative research or PhD • Strong Programming skills e.g. Python, R, SQL or other languages • Knowledge of predictive modeling, statistical distribution, monte calo simulation, machine learning and artificial intelligence techniques • Strong technical writing, communication and presentation skills and ability to effectively communicate quantitative topics with non-technical audiences • Experience with operational risk • Effective at prioritization/time and project management • Broad understanding of financial products Shift: 1st shift (United States of America) Hours Per Week: 40