Bank of America
Sustainability Sr. Quantitative Financial Analyst (CFO)
Bank of America, Charlotte, North Carolina, United States, 28245
Job Description:
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.
Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
This job is responsible for conducting quantitative analytics and complex modeling projects for specific business units or risk types. Key responsibilities include leading the development of new models, analytic processes, or system approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations may include the ability to influence strategic direction, as well as develop tactical plans.
The role is responsible for building data processes, data research and analytics, supporting model input monitoring and developing necessary reporting frameworks to support our approach to Net Zero, target setting, client engagement and risk review, empowering banking teams to assist clients on Net Zero financing strategies and specific commercial opportunities. The role will support and partner with business stakeholders and will support data governance, lineage, controls by building, improving and executing data processes. Candidate must be able to communicate across technology partners, the business lines, model development teams and Model Risk Management to execute on viable analytical solutions, with a focus on end-user experience and usability. Candidate must be strong in identifying and explaining data quality issues to help achieve successful and validated data for model execution.
Responsibilities
Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
Leads the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
Maintains and provides oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
Leads and provides methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
Create complex SQL queries and extract large, raw datasets from various sources, merging, and transforming raw data into usable data and analytic structures, and benchmarking results
Automate repeatable process, generating data insights that are easy for end users to interpret, conduct quantitative analysis, as well as effectively communicate and disseminate findings and data points to stakeholders
Evaluate options and finalize requirements in partnership with technology partners and product owners for development of strategic input sourcing of new model inputs or existing tactical inputs
Required Qualifications
5+ years experience in statistical and/or data management and analytics and visualization
Bachelor’s degree in accounting, finance or quantitative analytics
Experience in data management or analytics, engineering, sustainability, finance or other related field
Understanding of corporate accounting data integrity considerations and risk management
Deep expertise in SQL, Excel, R, Alteryx, automation & optimization and project management
Desired Qualifications
Financial Services Experience
Advanced degree or certification
Familiarity with data science, earth/climate sciences, engineering, sustainability, natural resource management, environmental economics, finance or other related field
Practical experience supporting data procurement and analytics of leading ESG reporting frameworks, specifically Sustainability Report and PCAF and experience with climate-related data providers and sources (S&P, MSCI, ERM etc.)
Knowledge of other frameworks and standards, including SASB, CDP, GRI and other impact reporting frameworks (IFC Performance Standards, Equator Principles, GIRS/IRIS, Impact Management Platform) and industry guidance (SBTi, NZBA, GFANZ, Transition Plan Taskforce, etc.) also welcome
Knowledge on Tableau and Python, (knowledge of NLP, data scraping and generative AI welcome)
Knowledge of data architecture concepts, data models, ETL processes
Experience in extracting, and combining data across from multiple sources, and aggregate data to support model development
Experience in multiple database environment such as Oracle, Hadoop, and Teradata
Skills
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
Shift 1st shift (United States of America)
Hours Per Week 40
#J-18808-Ljbffr
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.
Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
This job is responsible for conducting quantitative analytics and complex modeling projects for specific business units or risk types. Key responsibilities include leading the development of new models, analytic processes, or system approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations may include the ability to influence strategic direction, as well as develop tactical plans.
The role is responsible for building data processes, data research and analytics, supporting model input monitoring and developing necessary reporting frameworks to support our approach to Net Zero, target setting, client engagement and risk review, empowering banking teams to assist clients on Net Zero financing strategies and specific commercial opportunities. The role will support and partner with business stakeholders and will support data governance, lineage, controls by building, improving and executing data processes. Candidate must be able to communicate across technology partners, the business lines, model development teams and Model Risk Management to execute on viable analytical solutions, with a focus on end-user experience and usability. Candidate must be strong in identifying and explaining data quality issues to help achieve successful and validated data for model execution.
Responsibilities
Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
Leads the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
Maintains and provides oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
Leads and provides methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
Create complex SQL queries and extract large, raw datasets from various sources, merging, and transforming raw data into usable data and analytic structures, and benchmarking results
Automate repeatable process, generating data insights that are easy for end users to interpret, conduct quantitative analysis, as well as effectively communicate and disseminate findings and data points to stakeholders
Evaluate options and finalize requirements in partnership with technology partners and product owners for development of strategic input sourcing of new model inputs or existing tactical inputs
Required Qualifications
5+ years experience in statistical and/or data management and analytics and visualization
Bachelor’s degree in accounting, finance or quantitative analytics
Experience in data management or analytics, engineering, sustainability, finance or other related field
Understanding of corporate accounting data integrity considerations and risk management
Deep expertise in SQL, Excel, R, Alteryx, automation & optimization and project management
Desired Qualifications
Financial Services Experience
Advanced degree or certification
Familiarity with data science, earth/climate sciences, engineering, sustainability, natural resource management, environmental economics, finance or other related field
Practical experience supporting data procurement and analytics of leading ESG reporting frameworks, specifically Sustainability Report and PCAF and experience with climate-related data providers and sources (S&P, MSCI, ERM etc.)
Knowledge of other frameworks and standards, including SASB, CDP, GRI and other impact reporting frameworks (IFC Performance Standards, Equator Principles, GIRS/IRIS, Impact Management Platform) and industry guidance (SBTi, NZBA, GFANZ, Transition Plan Taskforce, etc.) also welcome
Knowledge on Tableau and Python, (knowledge of NLP, data scraping and generative AI welcome)
Knowledge of data architecture concepts, data models, ETL processes
Experience in extracting, and combining data across from multiple sources, and aggregate data to support model development
Experience in multiple database environment such as Oracle, Hadoop, and Teradata
Skills
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
Shift 1st shift (United States of America)
Hours Per Week 40
#J-18808-Ljbffr