Quantitative Finance Analyst

Bank of America•Atlanta, GA

1d•Onsite

About The Position

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. Enterprise Model Risk Management is seeking a Quantitative Finance Analyst to conduct independent model validation, independent testing and review of complex models used to monitor and mitigate money laundering risk. The ideal candidate should be familiar with industry practices and have knowledge of up-to-date AML techniques. The candidate should also be able to provide hands-on expertise in methodology, techniques, and processes in applying statistical and machine learning methods to manage the bank’s AML models and model systems. The qualified candidate will be responsible for a broad range of model validation activities, including: Review, critical assessment, and challenge of models on conceptual soundness, assumptions and limitations, data, developmental evidence in support of modeling choices, performance, implementation, and documentation. Development and implementation of effective testing plans and testing code to critically challenge models through empirical analyses and to verify model implementation. Performing model review activities including but not limited to independent model validation/challenge, annual model review, ongoing monitoring report review, required action item review, and peer review. Conducting governance activities such as model identification, model approval and breach remediation reviews to manage model risk. Communicating and working directly with relevant modeling teams and their corresponding Front Line Units; and if needed, communicating, and interacting with the third line of defense (e.g., internal audit) as well as external regulators. Writing technical reports for distribution and presentation to model developers, senior management, audit, and banking regulators Acts as a subject matter expert on analytic/quantitative modeling techniques used for Anti-money laundering.

Requirements

Master's degree or equivalent in Economics, Statistics, Finance, or related.
2+ years of experience in the job offered or a related Quantitative occupation.
Utilizing current modeling and data science principals including time-series analysis, machine learning and deep learning to validate financial crime detection models.
Applying statistical techniques to analyze trends and uncover risks and opportunities relative to anti-money laundering detection.
Supporting independent model validation and regulation exam activities in accordance with internal policies and U.S. Federal Reserve regulations.
Evaluating quantitative modelling and analytics projects through risk analytics.
Providing governance oversight for several financial crime detection models for model risk management.

Nice To Haves

Familiarity with industry practices and knowledge of up-to-date AML techniques.
Credible Challenge
Technical Documentation
Products, Services & Acumen - Line of Business (LoB) - GFC AML
Technical Modelling
Model Translation & Articulation
Model Validation & Governance
Technical Modelling
AML Regulatory Knowledge
Financial Crimes Risk Principles
Financial Crimes Risk Programs
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

Conducting quantitative analytics and modeling projects for specific business units or risk types.
Developing new models, analytic processes, or systems approaches.
Creating technical documentation for related activities.
Working with Technology staff in the design of systems to run models developed.
Conducting independent model validation, independent testing and review of complex models used to monitor and mitigate money laundering risk.
Providing hands-on expertise in methodology, techniques, and processes in applying statistical and machine learning methods to manage the bank’s AML models and model systems.
Review, critical assessment, and challenge of models on conceptual soundness, assumptions and limitations, data, developmental evidence in support of modeling choices, performance, implementation, and documentation.
Development and implementation of effective testing plans and testing code to critically challenge models through empirical analyses and to verify model implementation.
Performing model review activities including but not limited to independent model validation/challenge, annual model review, ongoing monitoring report review, required action item review, and peer review.
Conducting governance activities such as model identification, model approval and breach remediation reviews to manage model risk.
Communicating and working directly with relevant modeling teams and their corresponding Front Line Units.
Communicating and interacting with the third line of defense (e.g., internal audit) as well as external regulators.
Writing technical reports for distribution and presentation to model developers, senior management, audit, and banking regulators.
Acting as a subject matter expert on analytic/quantitative modeling techniques used for Anti-money laundering.