Sr. Quantitative Engineer

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: This job is responsible for designing and overseeing common, reusable, and scalable software components which are either domain independent (e.g., generic data quality tools over billions of rows of data) or domain specific (e.g., classification models for surveillance or testing framework for Global Markets processes). Key responsibilities include enabling Global Risk Management's data and analytical capabilities. Job expectations include working with senior modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics. Responsibilities: Seeks opportunities for consistent improvement in quality, efficiency, and processes Partners effectively with senior stakeholders within Global Risk Analytics and Enterprise Independent Testing, Front Line Units, Technology, Audit and Compliance Provides leadership and oversight to less experienced team members Applies quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements Understands financial data: schemas, flow, size, data issues, data controls, etc. Builds performant big data pipelines Uses programming skills and knowledge of software development lifecycle principles to deliver high quality code for model and testing processes Senior Quantitative engineers in Global Risk are responsible for designing and overseeing the implementation of common, reusable, and scalable software components. These components enable GRM’s data and analytical capabilities. These components can be domain independent (e.g., generic data quality tools over  billions of rows of data) or domain specific (e.g., classification models for surveillance or testing framework for Global Markets processes). Senior Quantitative engineers work with senior modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics. Senior Quantitative engineers have a combination of software engineering, big data, modeling and management 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. Job Responsibilities: Seek opportunities for consistent improvement in quality, efficiency, and processes Partner effectively with senior stakeholders within GRA & EIT, Front Line Units, Technology, Audit and Compliance Provide leadership and oversight to less experienced team members 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 models and tests for internal and regulatory purposes Technical skills: Software engineering: modular code, software lifecycle processes, unit testing, regression testing Big data: distributed computing paradigms (e.g., mapreduce, dataframes, etc), optimizing distributed software Modeling / quantitative: basic modeling techniques (regression, classification, clustering, etc.) Soft Skills: High level of intellectual curiosity Experience implementing strategic process improvements and/or automation  Proven track record of building relationships and effectively influencing key stakeholders  Adept at detecting and remediating organizational / process weaknesses and deficiencies Feels ownership and accountability for delivering high quality work, able to balance multiple priorities and meet strict deadlines  Strong written, verbal, presentation creation and delivery skills, typically to very senior audiences Well organized with attention to detail Willing to challenge the status quo and with a track record o