Quantitative Finance Analyst

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM). GRA is responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across Bank of America. GRA partners with the Lines of Business and Enterprise functions to ensure that its models and analytics address both internal and regulatory requirements, such as quarterly Enterprise Stress Testing (EST), the annual Comprehensive Capital Analysis and Review (CCAR), and the Current Expected Credit Losses (CECL) accounting standard. In addition to model development, GRA conducts model implementation, data management, model execution and analysis, forecast administration, and model performance monitoring. The team drives innovation, process improvement and automation across all of these activities.

Team Overview:

Wholesale Risk Analytics (within GRA) provides the decision support framework to translate data into actionable insights, support responsible growth and improve our business and risk partner’s ability to manage risk proactively. 

The WRA team is responsible for analytics and forecasting related to the Bank’s $500 billion plus commercial loan portfolio, playing a critical role in the Bank’s stress testing, financial planning, and risk management activities.

The Advanced Analytics function within WRA is responsible for developing the next generation of analytical tools and capabilities that provide forward-looking insights which go beyond first-order relationships and impacts. Advanced Analytics team members possess a combination of quantitative and qualitative skills and interact with a wide variety of stakeholders including members of quantitative model development teams, model execution / operations teams, forecast administers, enterprise and front line risk partners, and front line business partners.

Overview of Role:

The selected candidate will be responsible for conceptualizing, implementing, and socializing structured solutions to ambiguous and complex business problems using a combination of proprietary and third-party data and quantitative techniques, including modern data science concepts and methodologies. The candidate will also have the opportunity to collaborate with team members to develop strategic capabilities that form the basis for future research and analysis. Lastly, all team members are expected collaborate with, and influence, members at and below their peer group in other functions inside and outside of the immediate organization.

Required Skills:

• Minimum of 2 years of professional experience in an analytical role (e.g., quantitative model developer) with a Masters or PhD in an analytical field (e.g., Economics, Mathematics, Engineering).
• Data management experience including sourcing, wrangling, analysis, and visualization.
• In-depth understanding of current modeling and data science principals including but not limited to time-series analysis, machine learning, and deep learning.
• Experience with the entire software development lifecycle (SDLC) including maintaining and improving existing codebases and peer review changes.
• Ability collaborate with and influence technical and non-technical team members and stakeholders.
• Ability to communicate findings and insights to executive audiences.
• Strong understanding of at least one object-oriented programming language with familiarity with the following languages: Python, R, and SQL.

Desired Skills:

• Experience and understanding of loan and lease products for commercial clients.
• Professional experience with the following database tools: Hadoop, Teradata, Exadata (Oracle).
• Professional experience with the following software / tools: Tableau, JIRA, LaTex, Alteryx.

Shift:

1st shift (United States of America)

Hours Per Week:

40