Sr Quantitative Finance Analyst

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 is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. 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 conducting quantitative analytics and complex modeling projects for specific business units or risk types. Key responsibilities include leading the implementation and development of new models, analytic processes, or system approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations may include the ability to influence strategic direction, as well as develop tactical plans.

Responsibilities:

• Turn modeler code into a highly scalable big-data production application

• Identify 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

• Lead and provide 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

• Work closely with model stakeholders and senior management with regard to communication of submission and validation outcomes

• Perform analysis on large datasets and interpret results using both qualitative and quantitative approaches

Minimum Education Requirement: Master’s degree in related field or equivalent work experience

Required Skills and Experience: Successful candidates will have a minimum 10 years relevant experience and will possess the following skills:

• Advanced big data software development skills in both python and spark

• Deep expertise in Loss and Risk Forecasting Automation: odds calculations, cash flow calculations, model monitoring, back testing, reporting, etc.

• Sees the broader picture and can identify new methods for doing things

• Experience with Linux operating system and command line tools

• Familiar with software design principles: separation of concerns, single responsibility, DRY, etc.

• Understanding of algorithms and data structures

• Experience with version control systems, i.e., Git

• Knowledge of SQL

• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences

• Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others

• Experience implementing models into various production environments

• Demonstrated leadership skills; Ability to exert broad influence among peers

• Strategic thinker that can understand complex business challenges and potential solutions

• Ability to work in a large, complex organization, and influence various stakeholders and partners

• Ability to work in a highly controlled and audited environment

Desired Skills and Experience: The ideal candidate will possess the following skills and experience: 

• GRA Core Platform (GCP) experience

• Familiar with systems architecture concepts: service based, layered, microservices, scalability patterns

• Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow

• Experience creating, optimizing, and debugging software solutions deployed into distributed computing environments (experience with Spark is a plus)

• Familiar with use of vectorization and data locality concepts to optimize software efficiency 

• Experience with high performance Python libraries, i.e., Numpy, Numba, Cython

• Experience with LaTeX

• Familiarity with SDLC tools: unit testing libraries, Jira, Jenkins

• Consumer Financial Product Industry experience

Skills:

• Critical Thinking

• Quantitative Development

• Risk Analytics

• Risk Modeling

• Technical Documentation

• Adaptability

• Collaboration

• Problem Solving

• Risk Management

• Test Engineering

• Data Modeling

• Data and Trend Analysis

• Process Performance Measurement

• Research

• Written Communications

Shift:

Hours Per Week: