Data Scientist II - Natural Language Processing (NLP)

Key Skills

HTML, JavaScript, Java Programming, Leadership, CSS, Python Programming, Django, SQL, Agile methodologies, Git, API, React.js, Data science techniques, JIRA, A/B Testing, Deep Learning, Data Modeling, Natural Language Processing (NLP), Docker, GANs, Elasticsearch, Flask, Red Hat OpenShift, Bitbucket, K-Means clustering, FastAPI

Job Description

The Chief Data Science Organization (CDSO) is looking for a Natural Language Processing (NLP) research associate that has a rare combination of skills that will allow us to push the leading edge in NLP research in the financial services domain. If you love the challenge of applying data science skills to creating innovative solutions, we’d like to talk to you.

Key Responsibilities:

• Individual contributor role enabling Artificial Intelligence (AI) research and development (R&D) at Bank of America
• Build, improve, and extend NLP capabilities for Line of Business and Control Function partners
• Contribute research and prototype implementations for our next-generation AI systems
• Research and evaluate innovative approaches to NLP problems
• Communicate findings, gaps, and opportunities to senior leaders in the organization
• Take models from development to production in collaboration with product engineers
• Take a leadership role in the data science community of experts, specifically in the NLP domain

Role Qualifications:

• Advanced degree (MS, PhD) in natural language processing, computer science, engineering, human-computer interaction, or equivalent experience
• 4+ years of analytics, financial modeling and/or AI/ML modeling experience, with 2+ years of NLP experience

Strong background in one or more of the following domains: Natural Language Processing (NLP), Natural Language Understanding (NLU), Natural Language Generation (NLG), Automatic Speech Recognition (ASR), Human-Computer Interaction (HCI)

• Experience with at least one NLP technique such as word embeddings (word2vec, GloVe, fasttext, Transformers), topic modeling (LSA/LSI, LDA, NMF), search (Elasticsearch, FAISS), dialogue systems/chat bots (Rasa, kore.ai), knowledge graphs
• Knowledge of machine learning algorithms such as dimensionality reduction (PCA, SVD, UMAP, t-SNE), decision trees, random forest, gradient boosted trees, logistic regression, DBSCAN, K-means, hierarchical clustering, deep learning (sequential models like RNN/LSTM, convolutional neural networks, attention-based transformers, GANs)
• Experience with the application of Deep Learning to NLP tasks
• Labeling, Annotation, and A/B evaluation experience with NLP models preferred (e.g., LabelStudio, Prodigy, Brat)
• Ability to collaborate within and between cross-functional teams; excellent communication skills
• Highly organized and experienced in leading/managing complex projects, initiatives, and development
• Ability to manage multiple and competing priorities· Experience with model governance and version control/agile processes like Confluence/Jira/Bitbucket/Git preferred
• Experience with containers (Docker, OpenShift) is preferred
• Web development and API experience preferred (e.g., HTML, CSS, JavaScript, Flask, React, Streamlit, Django, FastAPI)