May 29, 2022
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New York, NY, United States
May 29, 2022
Apply NowJob description
Overview
Overview:
Comprehensive Capital Analysis & Review (CCAR) is a Federal Reserve requirement to perform stress testing to demonstrate banks have sufficient capital to withstand a severe economic stress event; results of the CCAR process inform firm’s ability to take capital actions such as paying dividends and share repurchases. Current Expected Credit Losses (CECL) is an approach used to calculate loan loss reserves reported on firm’s SEC financial statements (e.g., 10K, 10Q). CCAR Tech Team implements and executes CCAR and CECL financial analytics models covering forecasting (Balance Sheet, Macroeconomic Factors, Expense and Fee Revenue, etc.) and calculation (Market & Credit Risks, Risk Weighted Assets, Stress Capital Buffer Ratio, etc.) using analytics platform (compute cluster, GPU cluster, Spark/Hadoop, JupyterHub, Machine Learning(ML) toolkits, REST API, Micro-Services).
Role:
We have an exciting opportunity for a talented Data Scientist to join our team in Pittsburg, PA/New York, NY. As data scientist within the CCAR Tech team, you will be working in a fast-paced environment to implement and provide risk model execution support for CCAR/CECL and our analytics platforms. You will gain a thorough understanding of CCAR/CECL risk models and related financial analytics, and use your skills and expertise for implementing risk models and investigating and supporting financial analytics work.
Deliver on increasing complex analytics working with a cross functional team to deliver data products in line with business needs. Collects, analyzes and communicate data insights from internal and external data sources and deliver insights with in standard framework that can be leverages to deliver business value. Leverages simple to advanced data techniques to support making decisions from data with limited guidance. Responsible for data projects from inception to delivery partnering with functional and subject mater experts.Defines, creates and maintains analytics digitally modeling business opportunities through the use of information and advanced algorithms. Conducts studies to provide additional facts needed to make informed decisions for organizational and functional business opportunities.Communicates effectively with technical and business staff. Develops reports, and prepares and delivers both informational and decision-seeking presentations.Stays abreast of organization and management changes and has in-depth knowledge of company practices relevant to data science products.Maintains knowledge of company's total computing environment and planned changes in order to develop meaningful data science products.Grow and develop skills across the 3 domain specialties: model science, feature science and Insight science capabilities. Stressing expertise in the core functional areas: Computer Programming, Math&Analytic Methodology, Distributed computing and communications of complex results.Contributes to the achievement of related teams' objectives
Responsibilities:
Collaborate with stakeholders throughout the organization to develop project plans of delivering objects and timelines of risk model development and implementation.
Implement and develop risk models in Python for regulatory stress testing submission and company risk management. Design and build the execution workflow of models to forecast Balance Sheet, Fee Revenues, Macroeconomic Factors, Expense and calculate risk metrics under various stress scenarios, sensitivity & attribution analysis.
Coordinate with business quants and functional users to implement models and coordinate coding, testing, implementation and documentation of financial models for CCAR/CECL, including credit risk, market risk, RWA and balance sheet forecasting models.
Develop processes and tools to monitor and analyze model performance to ensure the expected application performance levels are achieved. Also, execute enterprise standards for model validation by applying statistical techniques and methodologies to test assumptions and review results of models.
Develop presentation decks using visual analytics tools and techniques. (JupyterHub/Python)
Apply data mining, data modelling and machine learning techniques to analyze large financial datasets and enhance the model performance.
Experience with complex quantitative modeling, numerical analysis, and computational method using one or more programming languages (Python, R, C++, Java, Matlab, etc.) and statistical/data manipulating software packages (Pandas, Scikit-Learn, MatPlotLib, SQL, etc)
Knowledge of advanced statistical techniques and concepts (regression, time series analysis, statistical models, etc.) is preferred
Experience working with market risk, credit risk or treasury risk models and financial products is preferred.
Qualification:
Bachelor's degree in a related discipline or equivalent work experience required 4-6 years of related experience required; experience in the securities or financial services industry is a plus.
BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals with Disabilities/Protected Veterans. Our ambition is to build the best global team – one that is representative and inclusive of the diverse talent, clients and communities we work with and serve – and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.
Employer Description:
For over 230 years, the people of BNY Mellon have been at the forefront of finance, expanding the financial markets while supporting investors throughout the investment lifecycle. BNY Mellon can act as a single point of contact for clients looking to create, trade, hold, manage, service, distribute or restructure investments and safeguards nearly one-fifth of the world's financial assets. BNY Mellon remains one of the safest, most trusted and admired companies. Every day our employees make their mark by helping clients better manage and service their financial assets around the world. Whether providing financial services for institutions, corporations or individual investors, clients count on the people of BNY Mellon across time zones and in 35 countries and more than 100 markets. It's the collective ambition, innovative thinking and exceptionally focused client service paired with a commitment to doing what is right that continues to set us apart. Make your mark: bnymellon.com/careers.
EEO Statement:
BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals With Disabilities/Protected Veterans. Our ambition is to build the best global team – one that is representative and inclusive of the diverse talent, clients and communities we work with and serve – and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.
Overview:
Comprehensive Capital Analysis & Review (CCAR) is a Federal Reserve requirement to perform stress testing to demonstrate banks have sufficient capital to withstand a severe economic stress event; results of the CCAR process inform firm’s ability to take capital actions such as paying dividends and share repurchases. Current Expected Credit Losses (CECL) is an approach used to calculate loan loss reserves reported on firm’s SEC financial statements (e.g., 10K, 10Q). CCAR Tech Team implements and executes CCAR and CECL financial analytics models covering forecasting (Balance Sheet, Macroeconomic Factors, Expense and Fee Revenue, etc.) and calculation (Market & Credit Risks, Risk Weighted Assets, Stress Capital Buffer Ratio, etc.) using analytics platform (compute cluster, GPU cluster, Spark/Hadoop, JupyterHub, Machine Learning(ML) toolkits, REST API, Micro-Services).
Role:
We have an exciting opportunity for a talented Data Scientist to join our team in Pittsburg, PA/New York, NY. As data scientist within the CCAR Tech team, you will be working in a fast-paced environment to implement and provide risk model execution support for CCAR/CECL and our analytics platforms. You will gain a thorough understanding of CCAR/CECL risk models and related financial analytics, and use your skills and expertise for implementing risk models and investigating and supporting financial analytics work.
Deliver on increasing complex analytics working with a cross functional team to deliver data products in line with business needs. Collects, analyzes and communicate data insights from internal and external data sources and deliver insights with in standard framework that can be leverages to deliver business value. Leverages simple to advanced data techniques to support making decisions from data with limited guidance. Responsible for data projects from inception to delivery partnering with functional and subject mater experts.Defines, creates and maintains analytics digitally modeling business opportunities through the use of information and advanced algorithms. Conducts studies to provide additional facts needed to make informed decisions for organizational and functional business opportunities.Communicates effectively with technical and business staff. Develops reports, and prepares and delivers both informational and decision-seeking presentations.Stays abreast of organization and management changes and has in-depth knowledge of company practices relevant to data science products.Maintains knowledge of company's total computing environment and planned changes in order to develop meaningful data science products.Grow and develop skills across the 3 domain specialties: model science, feature science and Insight science capabilities. Stressing expertise in the core functional areas: Computer Programming, Math&Analytic Methodology, Distributed computing and communications of complex results.Contributes to the achievement of related teams' objectives
Responsibilities:
Collaborate with stakeholders throughout the organization to develop project plans of delivering objects and timelines of risk model development and implementation.
Implement and develop risk models in Python for regulatory stress testing submission and company risk management. Design and build the execution workflow of models to forecast Balance Sheet, Fee Revenues, Macroeconomic Factors, Expense and calculate risk metrics under various stress scenarios, sensitivity & attribution analysis.
Coordinate with business quants and functional users to implement models and coordinate coding, testing, implementation and documentation of financial models for CCAR/CECL, including credit risk, market risk, RWA and balance sheet forecasting models.
Develop processes and tools to monitor and analyze model performance to ensure the expected application performance levels are achieved. Also, execute enterprise standards for model validation by applying statistical techniques and methodologies to test assumptions and review results of models.
Develop presentation decks using visual analytics tools and techniques. (JupyterHub/Python)
Apply data mining, data modelling and machine learning techniques to analyze large financial datasets and enhance the model performance.
Experience with complex quantitative modeling, numerical analysis, and computational method using one or more programming languages (Python, R, C++, Java, Matlab, etc.) and statistical/data manipulating software packages (Pandas, Scikit-Learn, MatPlotLib, SQL, etc)
Knowledge of advanced statistical techniques and concepts (regression, time series analysis, statistical models, etc.) is preferred
Experience working with market risk, credit risk or treasury risk models and financial products is preferred.
Qualification:
Bachelor's degree in a related discipline or equivalent work experience required 4-6 years of related experience required; experience in the securities or financial services industry is a plus.
BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals with Disabilities/Protected Veterans. Our ambition is to build the best global team – one that is representative and inclusive of the diverse talent, clients and communities we work with and serve – and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.
Employer Description:
For over 230 years, the people of BNY Mellon have been at the forefront of finance, expanding the financial markets while supporting investors throughout the investment lifecycle. BNY Mellon can act as a single point of contact for clients looking to create, trade, hold, manage, service, distribute or restructure investments and safeguards nearly one-fifth of the world's financial assets. BNY Mellon remains one of the safest, most trusted and admired companies. Every day our employees make their mark by helping clients better manage and service their financial assets around the world. Whether providing financial services for institutions, corporations or individual investors, clients count on the people of BNY Mellon across time zones and in 35 countries and more than 100 markets. It's the collective ambition, innovative thinking and exceptionally focused client service paired with a commitment to doing what is right that continues to set us apart. Make your mark: bnymellon.com/careers.
EEO Statement:
BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals With Disabilities/Protected Veterans. Our ambition is to build the best global team – one that is representative and inclusive of the diverse talent, clients and communities we work with and serve – and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.
