Drive the bank’s adoption of Generative AI by leveraging Large Language Models (LLMs) to solve business problems, enhance customer experiences, and streamline internal operations.
Requirements
- Strong proficiency in Python and experience working in notebook environments.
- Experience with NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face).
- Demonstrated ability to work with unstructured text data and apply text processing techniques.
- Experience sourcing and preparing data from various systems and formats.
- Exposure to Generative AI tools and pre-trained LLMs (e.g., GPT, Claude, Gemini).
- Exposure to creating agentic workflows and systems.
- Familiarity with prompt engineering and evaluation of LLM outputs.
Responsibilities
- Apply LLMs and other Generative AI tools to solve real-world problems across the bank, including summarization, classification, information extraction, and conversational AI.
- Source, clean, and prepare structured and unstructured data for model input and evaluation.
- Conduct exploratory data analysis and apply statistical techniques to support model evaluation and refinement.
- Stay current with advancements in Generative AI and NLP, and assess their applicability to banking use cases.
- Document methodologies, findings, and model usage clearly for both technical and non-technical audiences.
Other
- Collaborate with cross-functional teams including risk, compliance, and model validation to ensure responsible AI usage.
- Master’s Degree in Computer Science, Mathematics, Statistics, or a related field.
- Experience interacting with model validation teams and regulators.
- Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related field.
- Hybrid: 4 days onsite at a Citizens Corporate Office, 1 day remote
