Principal Data Intelligence Analyst, SPIS

General Description: The Principal Data Intelligence provides technical leadership and owns solution delivery from business requirements and architecture through prototyping, validation, production deployment, and adoption at scale; partners with business, domain, and technology stakeholders to prioritize high-value opportunities, establish engineering standards, and advance reusable AI capabilities. Essential Functions of the Job: AI Planning and Business Implementation: identify and prioritize high-value AI opportunities across clinical development and related business functions; translate business needs into technical solutions, product requirements, and AI capability roadmaps; define success criteria and drive measurable improvements in business process efficiency and quality through AI and automation. Agent and Platform Component Development: lead the architecture, hands-on development, and delivery of reusable AI skills, AI agents, platform components, and enterprise-grade AI solutions; apply LLMs, prompt engineering, RAG, agentic AI, multimodal AI, and knowledge graphs as appropriate; design and implement agent capabilities including context management, memory, planning, tool use, MCP integration, and multi-agent collaboration; own delivery from prototyping and validation through production deployment and adoption at scale. Model Training and Performance Optimization: define and execute model selection, adaptation, and optimization strategies; lead or contribute to data processing and annotation, fine-tuning, SFT, RL, and RLHF, with pretraining activities where appropriate; optimize inference and model services to improve accuracy, reliability, performance, and cost efficiency. Evaluation and Continuous Improvement: partner with business and domain experts to define evaluation criteria, develop evaluation datasets, and establish reproducible testing and release processes; implement monitoring and user-feedback loops to improve prompts, retrieval, knowledge bases, and agent orchestration; conduct technical research and proof-of-concept studies to assess emerging technologies and validate business value. Technical Leadership and Engineering Quality: establish reusable design patterns, technical documentation, and engineering best practices; conduct design and code reviews, provide technical guidance to colleagues, and collaborate with relevant teams to address security, privacy, governance, and operational requirements Supervisory Responsibilities: This is an individual contributor role focused on hands-on development and technical delivery. Technical leadership and mentoring do not include formal people-management responsibilities. Computer Skills: Strong foundation in machine learning, deep learning, computer science, and software engineering; Proficiency in Python and demonstrated ability to develop maintainable, tested, production-quality code; Hands-on experience across the AI/ML lifecycle, including development, evaluation, deployment, and monitoring; Practical experience with LLM applications, prompt engineering, RAG, vector search, knowledge bases, and workflow orchestration; Strong understanding of agent architectures and capabilities, including context management, memory, planning, tool use, MCP integration, and multi-agent collaboration; Knowledge of LLM fine-tuning and post-training techniques, such as SFT, RL, or RLHF; Experience deploying and supporting production AI/ML solutions, AI agents, or large-scale automation. Experience with Azure, AWS, Databricks, GCP, or Alibaba Cloud, Docker, Kubernetes, CI/CD, MLOps/LLMOps, and R programming language. Other Qualifications: At least 3 years of relevant experience in AI, ML, NLP, or software engineering, with demonstrated technical leadership and hands-on experience delivering production-grade AI solutions. Strong business acumen and ability to translate ambiguous business needs into practical technical solutions; Demonstrated ownership, sound technical judgment, and ability to deliver complex projects with a high degree of independence; Initiative, curiosity, an innovative mindset, attention to detail, and commitment to quality; Excellent teamwork, stakeholder collaboration, and technical communication skills, including effective verbal and written communication in both English and Chinese; An AI-native mindset, with the ability to use AI tools effectively and responsibly to improve development productivity; Experience in pharmaceuticals, biotechnology, clinical development, or clinical data processing and analysis is a plus. Travel: Occasional travel may be required to support business needs. 百济神州全球胜任力 当我们通过以下十二项全球胜任力，展现出 "患者为先"、"无界协作"、"锐意创新 "和 "追求卓越 "的价值观时，我们就能帮助全世界更多患者获得更多负担得起的药品。 ●团队协作 ●提供并征求坦诚及可行的反馈 ●自我认知 ●兼容并蓄 ●积极主动 ●开拓精神 ●持续学习 ●拥抱变化 ●结果导向 ●分析性思维/数据分析 ●卓越财务 ●清晰沟通 BeOne Global Competencies When we exhibit our values of Patients First, Collaborative Spirit, Bold Ingenuity and Driving Excellence, through our twelve global competencies below, we help get more affordable medicines to more patients around the world. ●Fosters Teamwork ●Provides and Solicits Honest and Actionable Feedback ●Self-Awareness ●Acts Inclusively ●Demonstrates Initiative ●Entrepreneurial Mindset ●Continuous Learning ●Embraces Change ●Results-Oriented ●Analytical Thinking/Data Analysis ●Financial Excellence ●Communicates with Clarity 求职者隐私申明： 百济神州致力于尊重和保护您的个人信息权利，并承诺依据合法、正当、必要和诚信的原则处理您的个人信息（包括个人敏感信息 ）。 由于百济神州在全球范围内开展业务，我们可能需要基于人力资源管理等合理业务目的而将您的个人信息发送和/或存储在位于您所在国家以外其他国家（例如：美国）的服务器和数据库中，详情参见百济神州《求职者隐私政策》（百济神州官网 - 隐私政策 - 求职者隐私政策）。 如您主动向我们提供您的简历信息或其他个人信息，则视为您已经充分理解并确认接受百济神州《求职者隐私政策》内容。如您对此有任何疑问的，请勿提交简历信息或其他个人信息。 BeOne is committed to respect and protect your personal information rights, and will process your personal information, including your sensitive personal information, based on the principles of legality, legitimacy, necessity, and integrity. 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