Quantitative Engineer

Bank of America; Jersey City (NJ); On-site; USD 90,000 - 156,000; Full time

Benefits offered by this job

Industry-leading benefits

Discretionary incentive

Job summary

Bank of America in Jersey City is seeking a quantitative engineer to design, develop, test and implement reusable software components for data quality tools and surveillance frameworks within Global Risk Analytics.

You will work with modelers, risk managers and technologists to shape the data and analytics roadmap, build big data pipelines, and contribute to regulatory-compliant modeling efforts.

Qualifications

• Bachelor’s degree in related field or equivalent work experience.
• 1-2 years of relevant professional experience or demonstrable coding projects.
• Strong Python development skills and SDLC knowledge.
• Experience with big data technologies and distributed computing.

Responsibilities

• Apply quantitative methods to develop capabilities meeting risk and regulatory requirements.
• Understand financial data schemas, flows, and data quality issues.
• Build and optimize big data pipelines for model and testing processes.
• Deliver high-quality code across data modeling and testing workflows.
• Collaborate with stakeholders to align modeling and testing needs.

Skills

Python

Spark

Hadoop

Pandas

React

JavaScript

Automation

Data Analytics

Education

Bachelor’s degree in related field

Tools

Hive

PySpark

SQL

Job description

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 from 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 impacting 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!

Bank of America is guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day. One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Job Description

This job is responsible for designing, developing, testing and implementing common, reusable, and scalable software components which are either domain independent (generic data quality tools over billions of rows of data) or domain specific (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 modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics.

Responsibilities

• 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
• Collaborates with key stakeholders across the Bank to understand modeling and testing business processes and requirements
• Thinks outside the box of current industry standards to develop innovative approaches
• Maintains and continuously enhances capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks

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, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA partners 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 drives innovation, process improvement and automation.

Job Description

Quantitative engineers in Global Risk are responsible for designing and implementing 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 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.

Job Responsiblities

• 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

Required Qualifications

• 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)
• 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
• A minimum of 1-2 years relevant professional experience or evidence of personal projects and endeavours that show a passion for coding and problem solving.
• Strong Programming skills (e.g., Python) and solid understanding of Software Development Life cycle principles
• Candidates should have at least one of these following skills and preferably have at least two of these skills:
  • Strong analytical and problem-solving skills
  • Experience applying quantitative methods such as modelling, data analytics, machine learning, and statistics to develop business solutions
  • Experience with large scale data sets with structured or unstructured data
  • Experience in building user facing applications over large amounts of data using technologies like React, Angular, JavaScript etc.
  • Experience implementing process improvements and automation
  • Strong Python development skills (including Pandas and related data-processing libraries)
  • Experience with big data technologies such as Spark, PySpark, Hadoop, and Hive
  • Exposure to quantitative modeling or financial modeling is a plus, but not required.

Skills

• Critical Thinking
• Data Modeling
• Process Effectiveness
• Risk Modeling
• Test Engineering
• Influence
• Oral Communications
• Prioritization
• Relationship Building
• Written Communications
• Attention to DetailChange Management

Minimum Education Requirement

Bachelor’s degree in related field or equivalent work experience

Shift

1st shift (United States of America)

Hours Per Week

40

Pay Transparency details

US - NJ - Jersey City - 525 Washington Blvd (NJ2525) Pay and benefits information Pay range $90,000.00 - $155,500.00 annualized salary, offers to be determined based on experience, education and skill set. Discretionary incentive eligible This role is eligible to participate in the annual discretionary plan.

Benefits

This role is currently benefits eligible. We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.

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