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.
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The Global Risk Analytics (GRA) group is a quantitative group and subline of Global Risk Management (GRM) which delivers models, tools, and analysis needed to effectively manage Risk and Capital. The Credit Loss Forecasts (CLF) team provides insights via credit loss forecasts and related portfolio, model and forecast analytics on Bank of America's approximately $500 billion consumer loan portfolio (including Mortgages, Credit Cards, and Auto loans). The Client Financial Health (CFH) team within Credit Loss Forecasts (CLF) leverages the power of BAC data to develop innovative and holistic approaches for consumer risk management, providing improved insights in changing or uncertain economic environments. The team conducts in-depth research of a wide range of topics and derive unique metrics from an internally developed research data mart. Meanwhile the CFH team collaborates with functions across the bank to identify customer risks, enhance GRA's analytical capabilities and provide contents on macro-economic trend reports that are widely viewed and quoted by media outlet. The right candidate will be someone who has intellectual curiosity and passion for seeking new and innovative ways of risk identification and assessment.
Responsibilities include:
- Provide subject matter expertise in the Bank's data, including but not limited to deposit and credit relationship, account and transactional data, as well as credit bureau data etc.
- Drive delivery of ideas and methodologies in "the what and how" insights can be extracted from the Bank's customer relationship data, to inform consumer financial health, economic trend, economic stress, inflation, income growth, unemployment, consumer behavior change in spending and finance, demographic shift, etc.
- Present key economic and credit insights gained from data research and analysis to credit executives, loss forecasting community and risk partners
- Provide data research and analysis support in use of the data across multiple functional areas, for instance, credit risk management and credit modeling across all consumer credit products, including credit card, small business card, auto loans, mortgage and home equity loans, as well as in general economy research, etc.
- Continue to build out and manage customer financial health database which houses customers' balance sheet and financial statement information, a major data source for credit risk analytics, execute process to deliver updated data to users
Required Qualifications:
Non-Technical
- Minimum of 5 years of relevant experience
- Strong communication and presentation skills, with the ability to adjust to both technical and executive audience
- Demonstrated ability to function independently and effectively in a matrix organization where success requires effective cross-functional-team collaboration
- Strong business acumen in consumer finance space
- Attention to detail
Technical
- Expertise in data research and analysis, navigation of data with complex linkage relationship stored across multiple data systems
- proficiency in SQL, Tableau, Python and SAS
- experience in big data processing on platform such as Teradata and Hadoop
Highly Desirable Qualifications:
- Data science / machine learning techniques
General Job Description:
This job is responsible for conducting quantitative analytics and complex modeling projects for specific business units or risk types. Key responsibilities include leading the development of new models, analytic processes, or system approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations may include the ability to influence strategic direction, as well as develop tactical plans.
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
- Leads 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
- Maintains and provides oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
- Leads and provides 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
- Written Communications
Minimum Education Requirement: Master's degree in related field or equivalent work experience
Shift:
1st shift (United States of America)
Hours Per Week:
40