药明生物
2027届-种子计划C-数字化（数据算法）-全球数智科技部
岗位职责
Data Collection & Cleaning: Collect and clean data based on business scenario
任职要求
to support analytics and model development
Data Analysis, Visualization & Presentation
Requirement Analysis & Algorithm Development: Conduct requirement analysis for business projects and design suitable algorithmic solutions, including but not limited to:
Machine Learning models, e.g., neural networks and reinforcement learning, tree-based models including classification and regression CART, Random Forest, GBM, XGBoost, LightGBM;
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;
LLM or LLM workflows on a large scale, with a deep understanding of Gen AI landscape
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 manner
AI Research & Innovation: Research and develop new AI technologies and optimize them for real business applications.
Software Development & Code Quality: Maintain good development practices to ensure that code is scalable, maintainable, and secure.
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:
Education: Bachelor, Master’s degree or above in Computer Science, Statistics, Mathematics, Bioinformatics, Computational Biology, or related fields.
Programming Skills: Solid in data structures, algorithms, and programming, with proficiency in Python.
AI/ML Frameworks: Familiarity with at least one deep learning framework, such as PyTorch or TensorFlow.
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.
Generative AI (LLM) Experience: Experience in developing and training large-scale models, especially with practical applications in the biopharmaceutical sector, is preferred.
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.
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.
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：
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
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
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
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
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。
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。
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：
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。
编程技能： 扎实的数据结构、算法和编程基础，熟练掌握Python。
AI/ML框架： 熟悉至少一种深度学习框架，如PyTorch或TensorFlow。
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。
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。
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。
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。
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
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