Sr. Quantitative Finance Analyst

Bank of America•Jersey City, NJ

4d•$125,000 - $210,000•Onsite

About The Position

Bank of America’s Enterprise Model Risk Management team is seeking a Senior Quantitative Finance Analyst to conduct independent model validation, testing, and review of complex models used to monitor and mitigate money laundering risk. The role requires familiarity with industry practices and current anti-money-laundering (AML) techniques, along with the ability to provide thought leadership and hands-on expertise in applying statistical and machine learning methods to manage AML models and model systems. The analyst reviews and challenges model soundness, assumptions, limitations, data, development evidence, performance, implementation, and documentation. The role also involves designing and implementing testing plans and code, conducting model and governance reviews, collaborating with modeling teams and business units, and communicating with internal audit or external regulators when needed. The analyst writes technical reports for model developers, senior management, audit, and banking regulators, and serves as a senior leader and subject matter expert on AML analytic and quantitative modeling techniques. This is a first-shift role with a 40-hour workweek. The listed work locations are Jersey City, New Jersey, and New York, New York. The annualized salary range is $125,000 to $210,000, with offers based on experience, education, and skill set. The role is eligible for an annual discretionary incentive plan and benefits, including paid time off and employee support resources.

Requirements

Advanced degree (PhD or master’s) in a quantitative field such as Mathematics, Physics, Finance, Economics, Engineering, Computer Science, Statistics, or a related field.
At least 5 years of experience and knowledge in building and understanding Anti-Money Laundering models and systems.
Strong, current familiarity with industry practices in AML techniques and typologies.
Domain knowledge of and familiarity with the regulatory landscape, including model risk management and anti-money laundering.
Advanced knowledge and working experience in statistical methods, techniques, and financial data.
Proficiency in Python, SAS, and SQL.
Strong written and verbal communication and collaboration skills.
Critical thinking and ability to work independently and proactively identify, debate, escalate, suggest, and resolve issues.

Nice To Haves

Proficiency with Above-the-Line and Below-the-Line (ATL/BTL) techniques, sampling methods, and AML coverage assessments.
Prior experience in model development and/or model validation.
CAMS certification.

Responsibilities

Review, critically assess, and challenge models’ conceptual soundness, assumptions and limitations, data, development evidence, performance, implementation, and documentation.
Develop and implement effective testing plans and testing code to challenge models through empirical analyses and verify model implementation.
Perform independent model validation and challenge, annual model reviews, ongoing monitoring report reviews, required action item reviews, and peer reviews.
Conduct governance activities, including model identification, model approval, and breach remediation reviews.
Communicate and work directly with modeling teams and their corresponding Front Line Units; interact with internal audit and external regulators when needed.
Write technical reports for model developers, senior management, audit, and banking regulators.
Act as a senior leader and subject matter expert on analytic and quantitative modeling techniques used for anti-money laundering.