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What You’ll Do： - Analyze assistant interactions, early usage data, and internal evaluations to identify improvement opportunities. - Generate data-driven insights to guide product development and feature prioritization. - Conduct research to improve agent architecture and user intent understanding to enhance response quality. - Design and execute experiments, identifying the right metrics to evaluate impact. - Collaborate with engineers and other Agent Science team members to implement and productionize improvements. - Leverage diverse datasets across ecosystem to improve assistant capabilities and deliver customer value. - Clearly communicate findings and contribute to research and product decisions. Basic Qualifications： - 3+ years of experience in data science, machine learning, or a related quantitative field. - Strong Python skills for data processing, analysis, and prototyping. - Proficiency in SQL and working with large-scale structured data. - Solid foundation in statistics, experimental design, and predictive modeling. - Ability to lead projects end-to-end and work effectively across teams. - Clear communicator with a proactive, problem-solving mindset. Preferred Qualifications： - Experience with conversational AI, NLP, or generative AI systems. - Familiarity with LLM evaluation methods and user interaction data. - Background in applied machine learning, cognitive science, or reinforcement learning. - Experience working in product-oriented, cross-functional environments.