岗位描述
Role Description:This position is part of the Global Digital Technologies Department. The team is composed of passionate experts from various fields such as research and development, AI, bioinformatics, product management， Enterprise platform, Information Security, and infrastructure. We uphold a spirit of craftsmanship to develop industry-leading digital platforms and tools, accelerating the speed and quality of drug discovery, development and manufacturing to ultimately improve human health. Key Responsibilities:1. Data Collection & Cleaning: Collect and clean data based on business scenario requirements to support analytics and model development2. Data Analysis, Visualization & Presentation3. Requirement Analysis & Algorithm Development: Conduct requirement analysis for business projects and design suitable algorithmic solutions, including but not limited to: (1) Machine Learning models, e.g., neural networks and reinforcement learning, tree-based models including classification and regression CART, Random Forest, GBM, XGBoost, LightGBM; (2) Optimization algorithms for NP-hard problems, e.g., Exact algorithm (Branch and Bound, Dynamic programing), Approximation, Heuristic (Greedy, Local Search), Metaheuristic (Genetic Algorithms) or Hybrid algorithm; (3) LLM or LLM workflows on a large scale, with a deep understanding of Gen AI landscape4. Model Implementation & Iteration: Quickly implement and deploy models, ensuring that they not only achieve sufficient prediction accuracy but also efficiently utilize computational resources and respond to requests in a timely manner5. AI Research & Innovation: Research and develop new AI technologies and optimize them for real business applications.6. Software Development & Code Quality: Maintain good development practices to ensure that code is scalable, maintainable, and secure.7. Team Collaboration & Support: Collaborate with cross-functional teams, including business teams, product managers, and developers, to deliver high-quality data solutions and support system deployment and issue resolution. Role Requirements:1. Education: Bachelor, Master’s degree or above in Computer Science, Statistics, Mathematics, Bioinformatics, Computational Biology, or related fields.2. Programming Skills: Solid in data structures, algorithms, and programming, with proficiency in Python.3. AI/ML Frameworks: Familiarity with at least one deep learning framework, such as PyTorch or TensorFlow.4. Model Development Experience: Understanding of common models such as NLP and GNN, with practical experience in natural language processing, deep learning, or knowledge graphs preferred.5. Generative AI (LLM) Experience: Experience in developing and training large-scale models, especially with practical applications in the biopharmaceutical sector, is preferred.6. Data Engineering Skills: Familiarity with SQL and NoSQL databases, experience with tools such as Hadoop, Hive, and Spark, and the ability to develop scalable data pipelines and applications.7. Communication & Teamwork: Strong communication skills, with the ability to collaborate effectively with cross-functional teams and a proactive attitude towards learning and problem-solving. Proficiency in Mandarin and English for work is a plus.8. Related Experience: Publications in NLP/AI-related international conferences or journals are preferred, as is experience in biopharmaceutical R&D.岗位说明：本岗位隶属于全球数智科技部，由一群热忱精英的研发、AI、生信、产品、企业平台、安全、基础设施等成员构成，我们保持工匠精神打造业内领先的数字化平台与工具，助推药物研发、制药开发及生产的速度与品质，服务人类生命健康。 岗位职责：1. 数据收集与清洗：根据业务场景需求，进行数据的收集与清洗，为数据分析、模型和算法的开发提供支持2. 数据分析、可视化与展示：根据业务场景需求，开展数据分析、定制可视化方案等3. 算法需求分析、设计和开发：负责业务项目的需求分析，设计并开发适合的算法解决方案，包括但不限于机器学习算法（如神经网络、强化学习、决策树、随机森林、GBM, XGBoost, LightGBM等），优化算法（如贪心算法、动态规划等），以及LLM大模型工程化部署等4. 模型实现与迭代：快速实现并部署模型，确保模型不仅具备足够的预测精度，还能高效利用算力，及时响应调用请求5. AI新技术研发：研究并开发新的AI技术，并结合实际业务问题进行优化。6. 软件开发与代码质量：保持良好的开发习惯，确保开发代码的可扩展性、可维护性和安全性。7. 团队协作与支持：与业务团队、产品经理、开发人员等团队合作，提供高质量的数据解决方案，并支持系统部署和问题解决。 岗位要求：1. 学历：计算机科学、统计学、数学、生物信息、计算生物学等相关领域的本科、硕士及以上学历。2. 编程技能：扎实的数据结构、算法和编程基础，熟练掌握Python。3. AI/ML框架：熟悉至少一种深度学习框架，如PyTorch或TensorFlow。4. 模型开发经验：理解并熟悉常见的NLP、GNN等模型原理，有自然语言处理、深度学习或知识图谱的实践经验者优先。5. 生成式人工智能(LLM)经验：具有开发和训练大模型的经验，特别是在生物医药领域的实际应用经验优先。6. 数据工程能力：熟悉SQL和NoSQL数据库，具备使用Hadoop、Hive、Spark等工具的经验，并能够开发可扩展的数据管道和数据应用。7. 沟通与团队合作：具有良好的沟通能力，能够很好地跨团队合作，并在学习和解决问题上有积极的态度。工作中可熟练使用英文者优先。8. 相关经验：在NLP/AI相关领域的国际会议或期刊上发表过文章者优先，生物医药研发相关经验优先。