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Gong is seeking a Senior Data Scientist to join the AI Research & Reliability team, working on cutting-edge LLM, NLP, and machine learning solutions that power the Gong Revenue AI Operating System. This role focuses on translating advanced AI research into scalable product experiences used by thousands of customers globally.
Key Responsibilities:
AI Product Lifecycle: Partner with Product and Engineering teams to translate customer and business needs into scalable AI solutions. Define AI approaches, agent architecture, success metrics, and technical strategy before implementation.
Agentic Systems: Design, build, and evaluate sub-agents, tools, retrieval systems, and memory architectures powering Gong AI Agents. Develop evaluation frameworks and benchmarks to measure workflow quality and continuously improve agent performance.
Conversational Intelligence: Analyze large-scale conversation data to uncover insights and develop NLP and LLM-based approaches that capture intent and nuance of human interactions.
Model & Pipeline Engineering: Build Python pipelines to create proprietary datasets, train and evaluate models, and integrate LLM-powered solutions into production systems serving millions of customer interactions.
Key Problem Areas:
Developing AI systems that reason over large-scale, unstructured customer interaction data, combining conversations, CRM signals, and other sources to uncover meaningful insights. Building intelligent agent experiences that handle retrieval, memory, reasoning, and evaluation to answer complex questions and deliver context-aware assistance. Extracting insights from conversations at scale using NLP and LLM techniques to identify intent, trends, and transform raw data into actionable intelligence. Experimenting with modern AI approaches including RAG, fine-tuning, clustering, and agentic workflows to solve real product challenges.
Required Qualifications:
M.Sc. in an exact science field (NLP or machine learning background preferred). 3+ years of industry experience in data science or machine learning with hands-on experience building AI and NLP solutions. Familiarity with modern AI approaches such as RAG, fine-tuning, agentic workflows, and LLM evaluation methods. Strong Python skills and experience with ML/data libraries (pandas, NumPy, scikit-learn, PyTorch, Transformers, LangChain, or similar). Experience designing experiments, analyzing results, and translating findings into product improvements. Strong analytical and problem-solving abilities.
