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.

• Execute monthly/quarterly data provisioning production processes as part of loss forecasting and enterprise stress testing.
• Perform and execute business controls during forecasting cycles and monitor and remediate incoming data issues.
• Maintain and develop new code /processes necessary to support data sourcing for model production.
• Support development and production of Global Risk Analytics Data Quality Controls dashboards, management reports, and ad hoc reporting.
• Respond to data related requests and ad hoc queries from business partners in timely fashion.
• Drive improvements in process via programming skills to automate processes and establish additional data analytics to improve data understanding.
• Analyze and evaluate large and complex economic and financial datasets with analytical tools Python and SQL.
• Use SQL to handle large volumes of data produced by complex financial forecasting models.
• Employ data analytics and visualization tools Alteryx, Tableau, and Jupyter Notebook to build easy access analytical capabilities and insightful reporting for the management.
• Implement advanced high-performance Python code for large-scale distributed computing environments of Apache Spark, Hadoop/HIVE to develop scalable, reusable analytical and quantitative models.
• Remote work may be permitted within a commutable distance from the worksite.

• Master's degree or equivalent in Statistics, Mathematics, Computer Science, or related; and
• 3 years of experience in the job offered or a related quantitative occupation.
• Must include 3 years of experience in each of the following:
• Analyzing and evaluating large and complex economic and financial datasets with analytical tools Python and SQL;
• Using SQL to handle large volumes of data produced by complex financial forecasting models;
• Employing data analytics and visualization tools Alteryx, Tableau, and Jupyter Notebook to build easy access analytical capabilities and insightful reporting for the management; and,
• Implementing advanced high-performance Python code for large-scale distributed computing environments of Apache Spark, Hadoop/HIVE to develop scalable, reusable analytical and quantitative models.