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Sr. Quantitative Finance Analyst

Bank of America

Bank of America

IT, Accounting & Finance
Posted on Friday, June 28, 2024

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. 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.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Job Description:

Enterprise Model Risk Management seeks a Senior Quantitative Finance Analyst to conduct independent review and testing of complex models based on artificial intelligence (AI) and machine learning (ML) techniques including natural language processing (NLP). These are high profile modelling areas in the bank, with continual senior management and regulatory focus. The Senior Quantitative Finance Analyst will be a key leader in Model Risk Management. The role is especially designed to provide both thought leadership and hands-on expertise in methodology, techniques, and processes in applying AI/ML models to manage the bank's large footprint in various line of businesses. The AI/ML model inventory cover areas of natural language processing, deep learning, ensemble learning, neural network, recommender systems and reinforcement learning. The model inventory is rapidly increasing especially with generative AI and large language models (LLMs). The methods include, but are not limited to, Regression, Gradient Boosting Tress, Random Forest, Artificial Neural Network and Transformer-based architectures.


  • Performing model review activities including but not limited to independent model validation/challenge, annual model review, ongoing monitoring report review, required action item review, and peer review.

  • Conducting governance activities such as model identification, model approval and breach remediation reviews to manage model risk.

  • Providing hands-on leadership for projects pertaining to statistical modeling and AI/ML approaches; and providing methodological, analytical, and technical support to effectively challenge and influence the strategic direction and tactical approaches of these projects.

  • Communicating and working directly with relevant modeling teams and their corresponding Front Line Units; and if needed, communicating, and interacting with the third line of defense (e.g., internal audit) as well as external regulators.

  • Writing technical reports for distribution and presentation to model developers, senior management, audit, and banking regulators.

  • Acts as a senior leader and Subject Matter Expert (SME) to help management’s decision making and guide junior team members.

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

Required Qualifications:

  • PhD or Masters in a quantitative field such as Mathematics, Physics, Engineering, Computer Science or Statistics.

  • Solid 3+ years of work experience at another financial service or technology firm in AI/ML, quantitative research, model development, and/or model validation.

  • Expert of AI/ML methodologies including NLP, e.g., methods in NLP used for text-to-text, speech-to-text/text-to-speech, and image-to-text tasks. Familiarity of techniques in generative AI and LLMs will be a great plus, e.g., prompt engineering, reinforcement learning from human feedback.

  • Proficient in Python, and ideally experienced in AI/ML packages, e.g., scikit-learn, TensorFlow, XGBoost, PyTorch, spaCy.

  • Domain knowledge such as retail banking, technology, operations, financial markets is a plus.

  • Strong knowledge of financial, mathematical, and statistical theories and practices, and a deep understanding of modeling process, model performance measures, and model risk of AI/ML models. Understanding of additional risks of AI/ML models in areas such as privacy or information security will be a plus.

  • Strong written and verbal communication skills and collaboration skills. This role involves communicating with various groups within the firm including stakeholders with non-technical background.

  • Critical thinking and ability to independently and proactively identify/suggest/resolve issues.

  • Motivated to continuously research and share state-of-the-art technologies, methodologies, and applications in the AI/ML field.


1st shift (United States of America)

Hours Per Week: