Quantitative Finance Analyst

Quantitative Finance Analyst

Chicago, Illinois;Jersey City, New Jersey; Charlotte, North Carolina; Atlanta, Georgia

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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 and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Job Description:

Bank of America Merrill Lynch has an opportunity for a Quantitative Finance Analyst within our Global Risk Analytics (GRA) function. Global Risk Analytics (GRA) is a sub-line of business within Global Risk Management (GRM), responsible for developing a consistent and coherent set of models and analytical tools for effective risk and capital measurement, management and reporting across the bank. GRA is also responsible for model implementation, execution, forecasting and performance monitoring. The team drives innovation, process improvement and automation across these activities.

The position is part of SERA's model development team, responsible for the creation and maintenance of models to produce risk ratings, behavior scores, forecasts, attributions and sensitivities for multiple use cases. The team follows the MDLC and validation is completed through partnership with MRM Model developers create best in class models and possess the skills needed to understand and evaluate data. They develop next-generational quantitative models and tools to support credit risk management and underwriting. As such, they are able to conduct produce professional research, transition conceptual frameworks into programming logic and communicate complex statistical, mathematical and financial topics to a wide range of audiences. A variety of quantitative and qualitative skills are required for these tasks. Models are developed utilizing multiple tools including Python, SQL, SAS, Hadoop and others. Typical techniques include data analysis, statistical regression analysis, Simulation, Cross-Section analysis, Stochastic analysis and Time-Series Analysis.

As a Quantitative Finance Analyst within the team, the main responsibilities will involve:

• Development of wholesale credit risk models including loss forecasting, commercial scorecards, behavioral score, regulatory capital models.

• Executing in-depth analysis of wholesale credit performance and financial data.

• Preparing white papers for developed models.

• Interacting with internal model risk management, addressing potential concerns, and remediating model related findings.

• Supporting post implementation activities including ongoing monitoring review and interaction with various stakeholders.

• Responsible for independently conducting quantitative analytics and complex modeling projects.

• Leads efforts in development of new models, analytic processes, or system approaches.

• Creates documentation for all activities and may work with technology staff in design of any system to run models developed. Incumbents possess excellent quantitative/analytic skills and can influence strategic direction, as well as develop tactical plans.

• Performing in-depth analysis on the Bank’s model results using various quantitative tools such as benchmarking, sensitivity analysis.

• Articulating the overall holistic picture of model performance, with clear conclusions regarding accuracy and remediation areas as required.

• Communicating model results to model stakeholders, including risk management, model development, model risk, senior management, and regulators.

Required Qualifications:

• Master’s degree in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline

• 5+ years professional experience developing credit risk models

• Strong Programming skills e.g. R, Python, SAS, SQL or other languages

• Strong analytical and problem-solving skills

• Experience using and developing cross-sectional models

• Experience implementing models into various production environments

• Effectively creates a compelling story using data; Able to make recommendations and articulate conclusions supported by data

• Effectively presents findings, data, and conclusions to influence senior leaders

• Demonstrated leadership skills; Ability to exert broad influence among peers

• Ability to work in a large, complex organization, and influence various stakeholders and partners

• Self-starter; Initiates work independently, before being asked

• Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others

• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences

• Ability to work in a highly controlled and audited environment

• Effective at prioritization, and time and project management

• Sees the broader picture and is able to identify new methods for doing things

• Strategic thinker that can understand complex business challenges and potential solutions

• Experience with complex data architecture, including modeling and data science tools and libraries, data warehouses, and machine learning

• Ability to extract, analyze, and merge data from disparate systems, and perform deep analysis

• Experience developing and maintaining complex databases and data sets

• Experience using data mining and other advanced analytical techniques to aggregate data for model development and/or to produce management reporting

• Experience managing large data sets utilizing tools such as Hadoop

• Experience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutions

• Experience with data analytics and visualization tools (e.g., Alteryx, Tableau, MicroStrategy)

• Experience with LaTeX

• Experience building data architecture that is optimized for large dataset retrieval, analysis, storage, cleansing, and transformation

• Demonstrated ability to drive action and sustain momentum to achieve results

• Identifies, assigns, and manages project tasks and timelines across teams

• Experience with engineering complex, multifaceted processes that span across teams

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

• Written Communications

Minimum Education Requirement: Master’s degree in related field or equivalent work experience

Shift:

1st shift (United States of America)

Hours Per Week:

40

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