Quantitative Finance Analyst

Bank of America•Jersey City, NJ

18h•$89,800 - $155,000•Onsite

About The Position

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!

Requirements

Masters' degree in Computer Science, Engineering, Mathematics, Statistics, Economics, Finance, Information Systems, or a related quantitative discipline.
4+ years of professional experience in software development, data engineering, analytics, or model operations.
Advanced Python programming experience with demonstrated ability to design, develop, troubleshoot, and support production-grade solutions.
Strong SQL skills with experience querying and validating large datasets.
Strong analytical and problem-solving skills with the ability to investigate issues independently and understand impacts across upstream and downstream processes.
Ability to quickly learn complex business processes and understand how multiple systems, models, and data flows interact.
Demonstrated success operating in a fast-paced environment with competing priorities and time-sensitive deliverables.
Strong attention to detail and personal ownership of work products.
Excellent verbal and written communication skills.
Ability to effectively collaborate across technology, quantitative, operational, and business teams.
Strong organizational skills with the ability to manage multiple initiatives simultaneously.

Nice To Haves

Experience supporting regulatory forecasting, stress testing, model execution, or financial risk management processes.
Experience with Tableau, Alteryx, or other visualization and reporting tools.
Understanding of governance, controls, audit, and compliance requirements within financial services.

Responsibilities

Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
Design, develop, and support Python-based solutions that automate production processes supporting forecasting, stress testing, and model execution activities.
Build and maintain data sourcing, transformation, monitoring, reporting, and post-model workflows sing python and Excel (mostly).
Develop scalable solutions using Python, SQL, and related technologies to improve efficiency, enhance controls, and reduce operational risk.
Investigate production issues, perform root cause analysis, and partner with technology and business teams to implement sustainable solutions.
Work closely with model developers, forecast administrators, technology teams, and business partners to understand business requirements and translate them into technical solutions.
Support model onboarding, model enhancements, GCP migrations, and production implementations across the SERA portfolio.
Develop and execute validation procedures to ensure accuracy and completeness of model inputs, outputs, and downstream reporting.
Create and maintain process documentation, operational procedures, controls, and governance artifacts supporting regulatory and audit requirements.
Identify opportunities to streamline workflows, eliminate manual processes, and improve production stability.
Participate in release testing, implementation activities, and ongoing support of quarterly and monthly forecast production cycles.
Contribute to a collaborative team environment that emphasizes continuous improvement, knowledge sharing, and operational excellence.