Distinguished, Data Scientist - Agent-Led Engagement in Conversational Commerce

• Design and implement models that drive agent-led engagement—including topic suggestion, conversation continuation, and goal-driven nudges—based on short-term context and long-term user understanding
• Develop LLM-based and hybrid (LLM + traditional ML) systems that detect high-value moments to engage and select relevant actions or content
• Build real-time ranking and decision systems that incorporate customer history, behavioral signals, and conversational state
• Define and prototype memory architectures that support persistent customer profiles and dynamic, evolving preferences
• Collaborate with platform and infra teams to integrate memory and decision modules into the end-to-end conversational stack
• Partner with product, UX, and engineering to surface proactive suggestions naturally and meaningfully within conversations
• Contribute to experimentation and evaluation frameworks to measure engagement, relevance, conversion, and long-term impact
• Review system-level decisions for safety, user experience, and brand alignment
• Act as a technical thought partner and advisor to the Director of Agent-Led Engagement and other senior leaders in agentic AI

• 7+ years of experience in data science, applied AI, or machine learning, with deep focus on personalization, conversational AI, or decision systems
• Demonstrated technical leadership in LLM-driven experiences, customer engagement modeling, or agentic applications
• Strong expertise in hybrid modeling (LLM + structured ML), dialogue state modeling, or sequential decision-making
• Experience designing or contributing to persistent memory systems for user modeling
• Proven ability to turn ideas into deployed, production-scale systems with measurable impact
• Strong communication and collaboration skills, with experience driving alignment across science, product, and engineering teams

• Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related field
• Experience in conversational commerce, recommendation systems, or task-oriented dialog agents
• Familiarity with contextual bandits, reinforcement learning, or user modeling at scale
• Experience working with memory-augmented LLMs or long-context transformer systems
• Track record of open-source contributions, publications, patents, or public speaking in applied AI or NLP

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Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.