Quantitative Finance Analyst
Newark, Delaware;Charlotte, North Carolina
Job Description:
Quantitative Financial Analyst – Consumer Loss Forecasting Data & Analytics
Overview of the Role / Job Description:
What would you like the power to do?
Bank of America’s Global Risk Analytics (GRA) organization has a high impact opportunity for a Quantitative Financial Analyst within its Consumer Loss Forecasting (CLF) team.
The GRA group is a quantitative group which delivers models, tools, and analysis needed to effectively manage Risk and Capital. The CLF team provides insights via credit loss forecasts and related portfolio, model and forecast analytics on Bank of America’s nearly $500 billion consumer loan portfolio (including Mortgages, Credit Cards, and Auto loans).
This role will play a critical part in the Bank’s financial planning, stress testing, credit risk allowance, and risk management activities, primarily by completing data and analytics projects that support loss forecasting. This role will interact with a wide variety of stakeholders including forecast administration, model operations & developers, allowance, risk and front line business unit. This position will focus on data extraction, conducting end to end analytics (MIS visualization, assessment) and driving data capability enhancements that aides risk management in the Card loss forecasting space. The position will mainly focus on the Card State Transition (CSTM) model that serves as champion in the CECL use case.
One large focus area relates to the broader adoption of the CSTM model as champion across the non-CECL use case. Given the model complexity and expanded adoption, it is critical to build out further knowledge of data, sub-models and key components of the CSTM model. This position will help partner across GRA and stakeholders to evolve the next generation process. Additionally, this position will support the Small Business Card Transition (SBCT) model build and deployment project for Loss Forecasting that will occur in 2023/2024.
The Analyst will help identify, lead, and organize data, analytics and strategic change efforts for Consumer Loss Forecasting. Some of those efforts include deployment of new models in the forecasting processes, knowledge expansion of the CSTM models, data extraction to support risk management assessment, and to improve existing reporting to enhance usability. The Analyst should be able to assess current data environment, innovate on end state capabilities, document key data flows, and partner across various stakeholder groups to enable improved business operations for the Card loss forecast.
As a Quantitative Finance Analyst within Global Risk Analytics, your main responsibilities will involve:
• Performing data analytics to support efforts to produce reasonable and supportable loss forecasts, and to provide deeper insight into consumer portfolios (Card, Business Card); this covers pulling data and telling a story that is engaging to management and stakeholders.
• Maintaining and continuously enhancing loss forecasting analytical processes and capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks.
• Understanding, executing and enhancing activities that form the end-to-end loss forecasting life cycle.
• Identifying requirements from the teams which improve the group’s ability to generate insights and understanding of portfolio risk, model accuracy, and forecast reasonability
• Clearly documenting and effectively communicating loss forecasting operations as part of ongoing engagement with key stakeholders.
Required Education, Skills & Experience:
2+ years of experience in data analytics, data aggregation, risk management, and quantitative research
Undergraduate degree in quantitative discipline (e.g. Science, Technology, Engineering, Mathematics, etc.)
Script language proficiency (Python, Hadoop, Spark, SQL, open source data science tools) to conduct analytical projects
Knowledge of modeling concepts through prior work and education experience
Strategic thinker that can understand complex business processes, data with high attention to detail; ability to optimize and streamline data, business processes
Be able to communicate complex quantitative results into a simple and concise story with senior managers.
Demonstrated ability to be collaborative, willingness to share knowledge with teammates
Able to document process steps, inputs/outputs, requirements, gaps & improve workflows
Desired Skills:
Master’s degree in financial, economic, data science or equivalent analytical discipline
Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
Able to develop data workflows and Tableau reporting suites with ability to prototype, test and iterate through report development
Strong business and financial acumen
Sees the broader picture and is able to identify process innovations
Strong team player able to seamlessly transition between contributing individually and collaborating on team projects
Job Band:
H5
Shift:
1st shift (United States of America)
Hours Per Week:
40
Weekly Schedule:
Referral Bonus Amount:
0
Job Description:
Quantitative Financial Analyst – Consumer Loss Forecasting Data & Analytics
Overview of the Role / Job Description:
What would you like the power to do?
Bank of America’s Global Risk Analytics (GRA) organization has a high impact opportunity for a Quantitative Financial Analyst within its Consumer Loss Forecasting (CLF) team.
The GRA group is a quantitative group which delivers models, tools, and analysis needed to effectively manage Risk and Capital. The CLF team provides insights via credit loss forecasts and related portfolio, model and forecast analytics on Bank of America’s nearly $500 billion consumer loan portfolio (including Mortgages, Credit Cards, and Auto loans).
This role will play a critical part in the Bank’s financial planning, stress testing, credit risk allowance, and risk management activities, primarily by completing data and analytics projects that support loss forecasting. This role will interact with a wide variety of stakeholders including forecast administration, model operations & developers, allowance, risk and front line business unit. This position will focus on data extraction, conducting end to end analytics (MIS visualization, assessment) and driving data capability enhancements that aides risk management in the Card loss forecasting space. The position will mainly focus on the Card State Transition (CSTM) model that serves as champion in the CECL use case.
One large focus area relates to the broader adoption of the CSTM model as champion across the non-CECL use case. Given the model complexity and expanded adoption, it is critical to build out further knowledge of data, sub-models and key components of the CSTM model. This position will help partner across GRA and stakeholders to evolve the next generation process. Additionally, this position will support the Small Business Card Transition (SBCT) model build and deployment project for Loss Forecasting that will occur in 2023/2024.
The Analyst will help identify, lead, and organize data, analytics and strategic change efforts for Consumer Loss Forecasting. Some of those efforts include deployment of new models in the forecasting processes, knowledge expansion of the CSTM models, data extraction to support risk management assessment, and to improve existing reporting to enhance usability. The Analyst should be able to assess current data environment, innovate on end state capabilities, document key data flows, and partner across various stakeholder groups to enable improved business operations for the Card loss forecast.
As a Quantitative Finance Analyst within Global Risk Analytics, your main responsibilities will involve:
• Performing data analytics to support efforts to produce reasonable and supportable loss forecasts, and to provide deeper insight into consumer portfolios (Card, Business Card); this covers pulling data and telling a story that is engaging to management and stakeholders.
• Maintaining and continuously enhancing loss forecasting analytical processes and capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks.
• Understanding, executing and enhancing activities that form the end-to-end loss forecasting life cycle.
• Identifying requirements from the teams which improve the group’s ability to generate insights and understanding of portfolio risk, model accuracy, and forecast reasonability
• Clearly documenting and effectively communicating loss forecasting operations as part of ongoing engagement with key stakeholders.
Required Education, Skills & Experience:
2+ years of experience in data analytics, data aggregation, risk management, and quantitative research
Undergraduate degree in quantitative discipline (e.g. Science, Technology, Engineering, Mathematics, etc.)
Script language proficiency (Python, Hadoop, Spark, SQL, open source data science tools) to conduct analytical projects
Knowledge of modeling concepts through prior work and education experience
Strategic thinker that can understand complex business processes, data with high attention to detail; ability to optimize and streamline data, business processes
Be able to communicate complex quantitative results into a simple and concise story with senior managers.
Demonstrated ability to be collaborative, willingness to share knowledge with teammates
Able to document process steps, inputs/outputs, requirements, gaps & improve workflows
Desired Skills:
Master’s degree in financial, economic, data science or equivalent analytical discipline
Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning
Able to develop data workflows and Tableau reporting suites with ability to prototype, test and iterate through report development
Strong business and financial acumen
Sees the broader picture and is able to identify process innovations
Strong team player able to seamlessly transition between contributing individually and collaborating on team projects
Shift:
1st shift (United States of America)
Hours Per Week:
40
Learn more about this role
Full time
JR-22093929
Band: H5
Manages People: No
Travel: No
Manager:
Talent Acquisition Contact:
Jillian Teeter
Referral Bonus:
0
Bank of America and its affiliates consider for employment and hire qualified candidates without regard to race, religious creed, religion, color, sex, sexual orientation, genetic information, gender, gender identity, gender expression, age, national origin, ancestry, citizenship, protected veteran or disability status or any factor prohibited by law, and as such affirms in policy and practice to support and promote the concept of equal employment opportunity and affirmative action, in accordance with all applicable federal, state, provincial and municipal laws. The company also prohibits discrimination on other bases such as medical condition, marital status or any other factor that is irrelevant to the performance of our teammates.
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