Quantitative Finance Analyst

Bank of America•Jersey City, NJ

4d•$89,800 - $155,000•Onsite

About The Position

Bank of America Merrill Lynch has an opportunity for a Quantitative Finance Analyst within our Global Risk Analytics (GRA) function. Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM), responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across the bank. GRA is also responsible for model implementation, execution, forecasting and performance monitoring. The team drives innovation, process improvement and automation across these activities. The position is part of SERA's model development team, responsible for the creation and maintenance of models to produce risk ratings, behavior scores, forecasts, attributions and sensitivities for multiple use cases. The team follows the MDLC and validation is completed through partnership with MRM Model developers create best in class models and possess the skills needed to understand and evaluate data. They develop next-generational quantitative models and tools to support credit risk management and underwriting. As such, they are able to conduct produce professional research, transition conceptual frameworks into programming logic and communicate complex statistical, mathematical and financial topics to a wide range of audiences. A variety of quantitative and qualitative skills are required for these tasks. Models are developed utilizing multiple tools including Python, SQL, SAS, Hadoop and others. Typical techniques include data analysis, statistical regression analysis, Simulation, Cross-Section analysis, Stochastic analysis and Time-Series Analysis.

Requirements

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

Nice To Haves

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

Responsibilities

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.
Responsible for independently conducting quantitative analytics and complex modeling projects.
Leads 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 and can influence strategic direction, as well as develop tactical plans.
Performing in-depth analysis on the Bank’s model results using various quantitative tools such as benchmarking, sensitivity analysis.
Articulating the overall holistic picture of model performance, with clear conclusions regarding accuracy and remediation areas as required.
Communicating model results to model stakeholders, including risk management, model development, model risk, senior management, and regulators.