Senior Analyst in Quantitative Finance

2 weeks ago

New York, New York, United States Bank of America Full time
Job Overview:

At Bank of America, we are driven by a shared mission to enhance financial well-being through every connection we foster. Our commitment to Responsible Growth shapes our operations and our dedication to serving clients, colleagues, communities, and shareholders alike.

We prioritize creating an inclusive and diverse workplace for all our employees globally. We seek individuals with varied backgrounds and experiences, investing significantly in our team members and their families by providing competitive benefits that support their overall well-being—physically, emotionally, and financially.

Bank of America recognizes the importance of collaboration while also offering flexibility tailored to the diverse roles within our organization.

Joining Bank of America means embarking on a rewarding career with ample opportunities for learning, growth, and impactful contributions, empowering you to make a difference.

Position Summary:

Enterprise Model Risk Management is looking for a Senior Analyst in Quantitative Finance to undertake independent evaluations and testing of intricate models utilizing artificial intelligence (AI) and machine learning (ML) methodologies, including natural language processing (NLP). These modeling domains are critical within the bank, attracting ongoing attention from senior management and regulatory bodies. The Senior Analyst will play a pivotal role in Model Risk Management, offering both strategic insights and practical expertise in methodologies, techniques, and processes for implementing AI/ML models across the bank's extensive operations. The AI/ML model portfolio encompasses areas such as natural language processing, deep learning, ensemble learning, neural networks, recommender systems, and reinforcement learning, with a rapidly expanding focus on generative AI and large language models (LLMs). The methodologies employed include, but are not limited to, Regression, Gradient Boosting Trees, Random Forest, Artificial Neural Networks, and Transformer-based architectures.

Key Responsibilities:
  • Conducting model review processes, including independent validation/challenge, annual assessments, ongoing monitoring reports, required action item reviews, and peer evaluations.
  • Executing governance activities such as model identification, approval processes, and breach remediation reviews to effectively manage model risk.
  • Providing expert leadership for projects related to statistical modeling and AI/ML strategies, offering methodological, analytical, and technical support to influence project direction and execution.
  • Engaging directly with relevant modeling teams and their corresponding units, and if necessary, liaising with internal audit and external regulatory bodies.
  • Drafting technical reports for distribution and presentation to model developers, senior management, audit teams, and regulatory authorities.
  • Serving as a senior leader and Subject Matter Expert (SME) to assist management in decision-making and mentor junior team members.
Educational Requirements:
Master's degree in a relevant field or equivalent professional experience.

Essential Qualifications:
  • PhD or Master's degree in a quantitative discipline such as Mathematics, Physics, Engineering, Computer Science, or Statistics.
  • A minimum of 3 years of relevant experience in a financial services or technology firm, focusing on AI/ML, quantitative research, model development, and/or validation.
  • Proficiency in AI/ML methodologies, particularly in NLP, including techniques for text-to-text, speech-to-text/text-to-speech, and image-to-text applications. Familiarity with generative AI and LLMs is advantageous.
  • Strong programming skills in Python, with experience in AI/ML libraries such as scikit-learn, TensorFlow, XGBoost, PyTorch, and spaCy.
  • Knowledge of domains such as retail banking, technology, operations, and financial markets is beneficial.
  • In-depth understanding of financial, mathematical, and statistical theories, along with a comprehensive grasp of modeling processes, performance metrics, and model risk associated with AI/ML models.
  • Excellent written and verbal communication skills, with the ability to collaborate effectively with diverse groups, including stakeholders with non-technical backgrounds.
  • Strong analytical and critical thinking skills, with a proactive approach to identifying and resolving issues.
  • A commitment to ongoing research and sharing of cutting-edge technologies, methodologies, and applications in the AI/ML sector.
Work Schedule:
1st shift (United States of America)

Weekly Hours:
40

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