Sr. Quantitative Financial Analyst

at Bank of America
Published January 6, 2022
Location Charlotte, NC
Category Default  
Job Type Full-time  

Description

Job Description:

At Bank of America, models are used for a broad range of activities, including but not limited to valuation, risk management, Anti-money laundering, Fair lending, liquidity planning, stress testing, underwriting, technology and operations and other strategic or day-to-day decision-making purposes. Bank of America recognizes the risk and uncertainty associated with the use of its models and the need to effectively manage this risk both at an individual level and in the aggregate. The Model Risk Management (MRM) Team provides oversight for model risk including artificial intelligence models across Bank of America's model inventory.  The MRM Team independently validates and challenges newly-developed and existing models; is responsible for model risk assessments, limits and monitoring; communicates issues identified through validations to relevant businesses and governance and control functions; and escalates model use breaches and remediation plans to relevant governance committees.

Enterprise Model Risk Management seeks a Senior Quantitative Finance Analyst to conduct independent testing and review of complex models used to support Global Technology and Operations activities. These are high profile modelling areas in the bank, with continual senior management and regulatory focus. The Senior Quantitative Finance Analyst will be a key leader in Model Risk Management. The role is especially designed to provide both thought leadership and hands-on expertise in methodology, techniques, and processes in applying statistical and machine learning models to manage the bank's large technology and operations footprint. These models include, but are not limited to, Regression, Gradient Boosting Tress, Random Forest, and Artificial Neural Network.

The position will be responsible for:
•    Performing all model validation tasks including but not limited to independent model validation, 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.
•    Providing hands-on leadership for projects pertaining to statistical modeling and machine learning approaches; and providing methodological, analytical, and technical support to effectively challenge and influence the strategic direction and tactical approaches of these projects.
•    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 senior level resource or resident expert on particular analytic/quantitative modeling techniques.

Required Qualifications & Skills:
•    PhD or Masters in a quantitative field such as Mathematics, Physics, Finance, Engineering, Computer Science or Statistics
•    Solid 3+ years of work experience at another financial services or technology firm in quantitative research, model development, and/or model validation.
•    Proficient in SAS and Python, and experienced in ML packages (e.g. sklearn, tensorflow, Xgboost)
•    Familiarity with technology processes and operations including information security, data privacy and protection, infrastructure and resiliency, virtual assistance, fraud prevention and related areas.
•    Domain knowledge in retail banking technology and operations is a plus, including the use of analytics to perform optical character recognition, automatic speech recognition, cyber risk monitoring, retail customer digital experience, ATM operations, and/or cash management. 
•    Strong knowledge of financial, mathematical and statistical theories and practices, and a deep understanding of the modeling process, model performance measures, and model risk.
•    Strong written and verbal communication skills and collaboration skills (this role involves communicating with various groups within the firm) 
•    Critical thinking and ability to independently and proactively identify/suggest/resolve issues
 

Job Band:

H4

Shift: 

1st shift (United States of America)

Hours Per Week:

40

Weekly Schedule:

Referral Bonus Amount:

0

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Job Description:

At Bank of America, models are used for a broad range of activities, including but not limited to valuation, risk management, Anti-money laundering, Fair lending, liquidity planning, stress testing, underwriting, technology and operations and other strategic or day-to-day decision-making purposes. Bank of America recognizes the risk and uncertainty associated with the use of its models and the need to effectively manage this risk both at an individual level and in the aggregate. The Model Risk Management (MRM) Team provides oversight for model risk including artificial intelligence models across Bank of America's model inventory.  The MRM Team independently validates and challenges newly-developed and existing models; is responsible for model risk assessments, limits and monitoring; communicates issues identified through validations to relevant businesses and governance and control functions; and escalates model use breaches and remediation plans to relevant governance committees.

Enterprise Model Risk Management seeks a Senior Quantitative Finance Analyst to conduct independent testing and review of complex models used to support Global Technology and Operations activities. These are high profile modelling areas in the bank, with continual senior management and regulatory focus. The Senior Quantitative Finance Analyst will be a key leader in Model Risk Management. The role is especially designed to provide both thought leadership and hands-on expertise in methodology, techniques, and processes in applying statistical and machine learning models to manage the bank's large technology and operations footprint. These models include, but are not limited to, Regression, Gradient Boosting Tress, Random Forest, and Artificial Neural Network.

The position will be responsible for:
•    Performing all model validation tasks including but not limited to independent model validation, 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.
•    Providing hands-on leadership for projects pertaining to statistical modeling and machine learning approaches; and providing methodological, analytical, and technical support to effectively challenge and influence the strategic direction and tactical approaches of these projects.
•    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 senior level resource or resident expert on particular analytic/quantitative modeling techniques.

Required Qualifications & Skills:
•    PhD or Masters in a quantitative field such as Mathematics, Physics, Finance, Engineering, Computer Science or Statistics
•    Solid 3+ years of work experience at another financial services or technology firm in quantitative research, model development, and/or model validation.
•    Proficient in SAS and Python, and experienced in ML packages (e.g. sklearn, tensorflow, Xgboost)
•    Familiarity with technology processes and operations including information security, data privacy and protection, infrastructure and resiliency, virtual assistance, fraud prevention and related areas.
•    Domain knowledge in retail banking technology and operations is a plus, including the use of analytics to perform optical character recognition, automatic speech recognition, cyber risk monitoring, retail customer digital experience, ATM operations, and/or cash management. 
•    Strong knowledge of financial, mathematical and statistical theories and practices, and a deep understanding of the modeling process, model performance measures, and model risk.
•    Strong written and verbal communication skills and collaboration skills (this role involves communicating with various groups within the firm) 
•    Critical thinking and ability to independently and proactively identify/suggest/resolve issues
 

Job Band:

H4

Shift: 

1st shift (United States of America)

Hours Per Week:

40

Weekly Schedule:

Referral Bonus Amount:

0

Job Description:
At Bank of America, models are used for a broad range of activities, including but not limited to valuation, risk management, Anti-money laundering, Fair lending, liquidity planning, stress testing, underwriting, technology and operations and other strategic or day-to-day decision-making purposes. Bank of America recognizes the risk and uncertainty associated with the use of its models and the need to effectively manage this risk both at an individual level and in the aggregate. The Model Risk Management (MRM) Team provides oversight for model risk including artificial intelligence models across Bank of America's model inventory.  The MRM Team independently validates and challenges newly-developed and existing models; is responsible for model risk assessments, limits and monitoring; communicates issues identified through validations to relevant businesses and governance and control functions; and escalates model use breaches and remediation plans to relevant governance committees.

Enterprise Model Risk Management seeks a Senior Quantitative Finance Analyst to conduct independent testing and review of complex models used to support Global Technology and Operations activities. These are high profile modelling areas in the bank, with continual senior management and regulatory focus. The Senior Quantitative Finance Analyst will be a key leader in Model Risk Management. The role is especially designed to provide both thought leadership and hands-on expertise in methodology, techniques, and processes in applying statistical and machine learning models to manage the bank's large technology and operations footprint. These models include, but are not limited to, Regression, Gradient Boosting Tress, Random Forest, and Artificial Neural Network.

The position will be responsible for:
•    Performing all model validation tasks including but not limited to independent model validation, 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.
•    Providing hands-on leadership for projects pertaining to statistical modeling and machine learning approaches; and providing methodological, analytical, and technical support to effectively challenge and influence the strategic direction and tactical approaches of these projects.
•    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 senior level resource or resident expert on particular analytic/quantitative modeling techniques.

Required Qualifications & Skills:
•    PhD or Masters in a quantitative field such as Mathematics, Physics, Finance, Engineering, Computer Science or Statistics
•    Solid 3+ years of work experience at another financial services or technology firm in quantitative research, model development, and/or model validation.
•    Proficient in SAS and Python, and experienced in ML packages (e.g. sklearn, tensorflow, Xgboost)
•    Familiarity with technology processes and operations including information security, data privacy and protection, infrastructure and resiliency, virtual assistance, fraud prevention and related areas.
•    Domain knowledge in retail banking technology and operations is a plus, including the use of analytics to perform optical character recognition, automatic speech recognition, cyber risk monitoring, retail customer digital experience, ATM operations, and/or cash management. 
•    Strong knowledge of financial, mathematical and statistical theories and practices, and a deep understanding of the modeling process, model performance measures, and model risk.
•    Strong written and verbal communication skills and collaboration skills (this role involves communicating with various groups within the firm) 
•    Critical thinking and ability to independently and proactively identify/suggest/resolve issues
 
Shift:

1st shift (United States of America)

Hours Per Week: 

40