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. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.
We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Job Description:
This job is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key responsibilities include developing new models, analytic processes, or systems approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations include having 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
As a Quantitative Finance Analyst on the team, your main responsibilities will involve:
Development of wholesale credit risk models including loss forecasting, commercial scorecards, behavioral score, regulatory capital models.
Executing in-depth analysis of wholesale credit performance and financial data.
Preparing white papers for developed models.
Interacting with internal model risk management, addressing potential concerns, and remediating model related findings.
Supporting post implementation activities including ongoing monitoring review and interaction with various stakeholders. May be responsible for independently conducting quantitative analytics and complex modeling projects. Support efforts in development of new models, analytic processes, or system approaches. Creates documentation for all activities and may work with technology staff in design of any system to run models developed. Incumbents possess excellent quantitative/analytic skills.
Required Qualifications:
Master’s degree in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline
5+ years professional experience developing credit risk models
Strong Programming skills e.g. R, Python, SAS, SQL or other languages
Strong analytical and problem-solving skills
Experience using and developing cross-sectional models
Experience implementing models into various production environments
Effectively creates a compelling story using data; Able to make recommendations and articulate conclusions supported by data
Effectively presents findings, data, and conclusions to influence senior leaders
Demonstrated leadership skills; Ability to exert broad influence among peers
Ability to work in a large, complex organization, and influence various stakeholders and partners
Self-starter; Initiates work independently, before being asked
Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others
Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
Ability to work in a highly controlled and audited environment
Effective at prioritization, and time and project management
Sees the broader picture and is able to identify new methods for doing things
Strategic thinker that can understand complex business challenges and potential solutions
Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis
Experience developing and maintaining complex databases and data sets
Experience using data mining and other advanced analytical techniques to aggregate data for model development and/or to produce management reporting
Experience managing large data sets utilizing tools such as Hadoop
Experience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutions
Experience with data analytics and visualization tools (e.g., Alteryx, Tableau, MicroStrategy)
Experience with LaTeX
Experience building data architecture that is optimized for large dataset retrieval, analysis, storage, cleansing, and transformation
Demonstrated ability to drive action and sustain momentum to achieve results
Identifies, assigns, and manages project tasks and timelines across teams
Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow.
Skills:
Minimum Education Requirement: Master’s degree in related field or equivalent work experience
Shift:
1st shift (United States of America)
Hours Per Week:
40
