Job Summary
We are seeking a highly technical Data Scientist to support an AI-enabled initiative focused on call center efficiency and customer experience. This role will focus on building, enhancing, troubleshooting, and evaluating deep learning and NLP models that analyze customer interactions across contact center calls, member service interactions, chat conversations, and digital engagement channels. The ideal candidate will have strong expertise in deep learning, NLP, Large Language Models (LLMs), Python, and SQL, with experience developing and evaluating AI models in production environments.
Key Responsibilities
• Build, enhance, troubleshoot, and evaluate deep learning and NLP models for customer and member service operations.
• Develop models that analyze customer interactions to identify contact drivers, customer intent, outcomes, emerging topics, and trends.
• Develop and maintain solutions for text classification, embeddings, clustering, topic modeling, and intent classification.
• Deploy and evaluate LLM-based solutions and fine-tune transformer-based models.
• Develop effective prompt engineering strategies and model evaluation frameworks.
• Identify and investigate hallucinations, reliability issues, and other AI model performance challenges.
• Troubleshoot model performance issues and conduct root cause analysis.
• Analyze noisy, incomplete, or limited training data and perform systematic debugging and error analysis.
• Continuously enhance model capabilities by introducing new topics, classifications, and intelligence layers into existing solutions.
• Analyze large volumes of unstructured data from contact center calls, member service interactions, chat conversations, and digital engagement channels.
• Develop insights that support opportunities to improve customer experience and reduce contact volume.
Required Qualifications
• Hands-on experience building and deploying deep learning models in production environments.
• Strong understanding of neural network architectures.
• Experience troubleshooting and optimizing deep learning model performance.
• Strong hands-on experience with Natural Language Processing (NLP).
• Experience with text classification, embeddings, clustering, topic modeling, and intent classification.
• Experience developing and evaluating NLP models.
• Experience deploying Large Language Model (LLM) solutions.
• Experience evaluating LLM outputs and fine-tuning transformer-based models.
• Experience with prompt engineering and building model evaluation frameworks.
• Experience identifying hallucinations and reliability issues in AI/LLM solutions.
• Strong experience with model diagnostics, root cause analysis, debugging, and error analysis.
• Strong proficiency in Python.
• Strong proficiency in SQL.
Preferred Qualifications
• Experience with contact center or customer experience analytics.
• Experience in the healthcare industry.
• Experience with Google Cloud Platform (GCP).
