Understanding customer feedback using Natural Language Processing (NLP) and Large Language Models (LLMs) to transform unstructured text into actionable insights for the Rewards and Loyalty Product team
Requirements
- Strong hands-on experience with NLP techniques (NER, topic modeling, text classification, etc.)
- Experience with LLM orchestration frameworks (LangChain, LangGraph, etc.)
- Exposure to GenAI services such as AWS Bedrock or Azure OpenAI
- Strong Python skills and experience with data processing libraries (Pandas, spaCy, HuggingFace, etc.)
- Experience working with customer experience data, complaints, or survey analytics
- Familiarity with prompt engineering and working with LLMs (OpenAI, Claude, etc.)
- Working knowledge of RAG architecture and Agentic AI concepts
Responsibilities
- Develop and maintain NLP/LLM pipelines to extract and classify customer feedback using custom taxonomies
- Write effective prompts and apply large language models (LLMs) to categorize and summarize unstructured text
- Collaborate on taxonomy development for complaint categorization and feedback analysis
- Implement and optimize topic modeling techniques to uncover emerging themes
- Explore and prototype use cases for GenAI across various business domains
- Integrate LLM frameworks and APIs using tools such as LangChain, LangGraph, and AWS Bedrock
- Experiment with Claude, OpenAI, and other foundational models to build intelligent assistants
Other
- Bachelor's degree in Computer Science, Engineering or related field (not explicitly mentioned but implied)
- Collaboration and teamwork skills (implied by 'Collaborate on taxonomy development')
- No travel requirements mentioned
- No visa requirements mentioned
- No specific soft skills mentioned beyond collaboration and teamwork
