Quantitative Finance Analyst

Bank of America•Charlotte, NC

6d•Onsite

About The Position

This job is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key responsibilities include developing new models, analytic processes, or systems approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations include having a broad knowledge of financial markets and products. 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

Bachelor’s degree in Finance, Accounting, Economics, Business, or related field. Alternatively. (i.e: engineering, computer science, mathematics, statistics, etc.) and a demonstrated interest in finance and markets.
Ability to identify key industry drivers, excellent quantitative skills and judgment in the field of research.
The candidate must be able to thrive in a fast-paced and intense environment, be intellectually curious about drivers of the economy, industry & company performance and consumer behavior
Strong economic and financial skills and a keen interest in markets, economics, and worldwide current events
Strong writing and spreadsheet skills
Must be an expert in MS Excel
Must have excellent communication skills, written and verbal
Must have strong attention to detail, ability to multi-task
Must work well in a collaborative team environment and be exceptionally driven

Nice To Haves

Masters in one of the aforementioned subjects a plus.
Progress toward (or completion of) CFA a plus.
experience working with statistical packages and/or programming experience preferred
Some knowledge of Tableau, SQL, Python.
Good understanding of current US regulatory environment

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
Production and model implementation support across SERA Ops team. Forecast Operations team members utilize their skills in data wrangling, process engineering, database management, and software development lifecycle project management to ensure that the processes to create forecasts is well controlled.
These team members leverage skills in quantitative methods to conduct ongoing monitoring of model performance.
They also possess capabilities in data science and data visualization techniques and tools.
Role will write Python and/or PySpark code to automate production processes of several risk and loss measurement statistical models; work closely with application users, model developers, technology and other business partners to understand and document requirements of production processes to be implemented; work with technology teams to integrate Python solution into existing in-house generic platform for process execution; ensure software is developed to meet functional, non-functional, and compliance requirements; write complex SQL queries to validate production results, integrate results with existing downstream applications and produce reports in format expected by end users and support GCP migrations and implementations across SERA portfolio.