Sr. Quantitative Engineer
About The Position
At Bank of America, the Sr. Quantitative Engineer designs and oversees the implementation of common, reusable, and scalable software components that enable Global Risk Management’s data and analytical capabilities. Components may be domain-independent, such as data-quality tools for large datasets, or domain-specific, such as classification models for surveillance or testing frameworks for Global Markets processes. The role works with senior modelers, risk managers, technologists, and other stakeholders to understand existing processes and design future-state data and analytics capabilities. It combines software engineering, big data, quantitative modeling, and management skills, with work spanning the big data stack from data and logic through models and user interfaces. The engineer develops and maintains modeling and testing capabilities that meet business, risk-management, and regulatory requirements, and produces clear, repeatable technical documentation. Bank of America describes its culture as focused on Responsible Growth, inclusion, collaboration, career development, and teammate well-being. The company states that it is committed to an in-office culture, with role-specific flexibility based on responsibilities and business needs. This position is based at 525 Washington Blvd, Jersey City, New Jersey. It is a first-shift role with 40 hours per week. The annual salary range is $140,000 to $215,500, with offers based on experience, education, and skill set. The role is eligible for an annual discretionary incentive plan and company benefits, including paid time off.
Requirements
- Bachelor’s degree in Computer Science, a closely related field, or a degree from a program where software engineering was a key focus, or equivalent work experience.
- At least 7 years of relevant experience in software engineering in Quantitative Finance or other industries.
- Strong programming skills, such as Python, and a solid understanding of software development lifecycle principles.
- Proven track record of seamlessly leading and executing enterprise-wide initiatives.
- Ability to explain the rationale and details of methodologies to senior stakeholders, auditors, and regulators.
- Strong analytical and problem-solving skills.
- Experience applying quantitative methods such as modeling, data analytics, machine learning, or statistics to develop business solutions; experience with large-scale structured or unstructured datasets; and/or experience building user-facing applications over large amounts of data using technologies such as React, Angular, or JavaScript. Candidates should have at least three of these listed skill areas.
- Experience with software engineering practices including modular code, software lifecycle processes, unit testing, and regression testing.
- Experience with big-data distributed computing paradigms, such as MapReduce or dataframes, and optimizing distributed software.
- Knowledge of basic modeling techniques such as regression, classification, or clustering.
- High intellectual curiosity.
- Experience implementing strategic process improvements and/or automation.
- Ability to build relationships and effectively influence key stakeholders.
- Ability to detect and remediate organizational or process weaknesses and deficiencies.
- Ownership and accountability for high-quality work, with the ability to balance priorities and meet strict deadlines.
- Strong written, verbal, and presentation creation and delivery skills, including communication to senior audiences.
- Well organized with attention to detail.
- Willingness to challenge the status quo and a track record of driving change.
Responsibilities
- Seek opportunities to improve quality, efficiency, and processes.
- Partner with senior stakeholders in Global Risk Analytics and Enterprise Independent Testing, Front Line Units, Technology, Audit, and Compliance.
- Provide leadership and oversight to less experienced team members.
- Apply quantitative methods to develop capabilities that meet line-of-business, risk-management, and regulatory requirements.
- Understand financial data, including schemas, data flows, scale, data issues, and controls.
- Build performant big-data pipelines.
- Use programming skills and software development lifecycle principles to deliver high-quality code for model and testing processes.
- Collaborate with stakeholders across the Bank to understand modeling and testing processes and requirements.
- Develop innovative approaches beyond current industry standards.
- Maintain and enhance capabilities in response to changes in portfolios, economic conditions, and emerging risks.
- Source and evaluate data for modeling and testing.
- Design, develop, and implement models and tests.
- Produce clear, concise, repeatable technical documentation for models and tests for internal and regulatory purposes.
Benefits
- Annual discretionary incentive plan eligibility
- Paid time off
- Company benefits eligible
- Resources and support for employee well-being
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What This Job Offers
Job Type
Full-time
Career Level
Senior
