Quantitative Engineer Analyst - Market Behavior Analytics Group

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!

Quantitative Engineer Analyst is the entry level role to becoming a Quantitative Engineer. Quantitative engineers in Global Risk are responsible for designing and implementing common, reusable, and scalable software components. These components enable GRMs data and analytical capabilities. These components can be domain independent (e.g., generic data quality tools over trillions of rows of data) or domain specific (e.g., classification models for surveillance or testing framework for Global Markets processes). Quantitative engineers work with modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics. Quantitative engineers have a combination of software engineering, big data, and modeling skills and the ability to work across the entire spectrum of a big data stack from data to logic to model to UI to UX.

Responsibilities:

• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements

• Understanding financial data: schemas, flow, size, data issues, data controls, etc.

• Building performant big data pipelines

• Use programming skills and knowledge of software development lifecycle principles to deliver high quality code for model and testing processes

• Collaborate with key stakeholders across the Bank to understand modeling and testing business processes and requirements

• Think outside the box of current industry standards to develop innovative approaches

• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks

• Source and evaluate data required for modeling and testing

• Design and develop and implement models and tests

• Produce clear, concise and repeatable technical documentation on models and tests for internal and regulatory purposes

Team Overview:

Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT) are sub-lines of business within Global Risk Management (GRM). Collectively, they are responsible for developing a consistent and coherent set of models, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA and EIT partner with the Lines of Business and Enterprise functions to ensure the capabilities it builds address both internal and regulatory requirements, and are responsive to the changing nature of portfolios, economic conditions, and emerging risks. In executing its activities, GRA and EIT drive innovation, process improvement and automation.

The Market Behavior Analytics group within Global Risk Analytics is responsible for developing surveillances and other sophisticated controls over activities in our Global Markets business. These controls detect potentially suspicious activities and patterns of behavior. Building these controls requires knowledge of big data techniques, ability to architect systems that can efficiently scale to hundreds of billions of data points per day, machine learning over unstructured and structured data, graph analytics, and experience with building UI for data rich applications.

Skills:

• High level of intellectual curiosity

• Feel ownership and accountability for delivering high quality work, able to prioritize effectively, adapt, and meet strict deadlines

• Strong written, verbal, presentation creation and delivery skills

• Well organized, and has attention to detail

• Ability to adjust to new conditions and changes effectively

• Capacity to notice and consider all aspects or a task or project

• Work effectively with others toward a common goal

Minimum Education Requirements:

• Bachelors degree in Computer Science, a closely related field, or a degree from a program where software engineering was a key focus

Qualifications:

• Strong Programming skills (e.g., Python)

• Strong analytical and problem-solving skills

• Digital fluency

Shift:

Hours Per Week:

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