The rapid advances of large language models (LLMs), such as ChatGPT, are revolutionizing data science and statistics. These state-of-the-art tools can streamline complex processes. As a result, it reshapes the role of data scientists. We argue that LLMs are transforming the responsibilities of data scientists, shifting their focus from hands-on coding, data-wrangling and conducting standard analyses to assessing and managing analyses performed by these automated AIs. This evolution of roles is reminiscent of the transition from a software engineer to a product manager. We illustrate this transition with concrete data science case studies using LLMs in this paper. These developments necessitate a meaningful evolution in data science education. Pedagogy must now place greater emphasis on cultivating diverse skillsets among students, such as LLM-informed creativity, critical thinking, AI-guided programming. LLMs can also play a significant role in the classroom as interactive teaching and learning tools, contributing to personalized education. This paper discusses the opportunities, resources and open challenges for each of these directions. As with any transformative technology, integrating LLMs into education calls for careful consideration. While LLMs can perform repetitive tasks efficiently, it's crucial to remember that their role is to supplement human intelligence and creativity, not to replace it. Therefore, the new era of data science education should balance the benefits of LLMs while fostering complementary human expertise and innovations. In conclusion, the rise of LLMs heralds a transformative period for data science and its education. This paper seeks to shed light on the emerging trends, potential opportunities, and challenges accompanying this paradigm shift, hoping to spark further discourse and investigation into this exciting, uncharted territory.

翻译：大语言模型（如ChatGPT）的快速发展正彻底改变数据科学与统计学领域。这些尖端工具能够简化复杂流程，从而重塑数据科学家的角色定位。我们认为，大语言模型正在转变数据科学家的职责范畴：从亲力亲为的编程、数据整理和标准分析，转向评估与管理由自动化人工智能执行的分析任务。这种角色演进类似于软件工程师向产品经理的转型。本文通过具体数据科学案例研究，结合大语言模型的应用，阐释了这一转型过程。这些发展要求数据科学教育进行深刻变革。教学法必须更加注重培养学生多元技能，包括基于大语言模型的创造力、批判性思维、人工智能辅助编程等。大语言模型还可以在课堂中扮演互动教学工具的重要角色，助力个性化教育。本文探讨了这些方向面临的机遇、资源与开放挑战。如同任何变革性技术，将大语言模型融入教育需要审慎考量。虽然大语言模型能高效执行重复性任务，但其作用应是增强而非取代人类智慧与创造力。因此，新时代的数据科学教育应在发挥大语言模型优势的同时，培养互补性的人类专长与创新。总之，大语言模型的崛起预示着数据科学及其教育领域正在经历变革期。本文旨在揭示伴随这一范式转变而来的新兴趋势、潜在机遇与挑战，期望能激发对这一激动人心未知领域的深入探讨与研究。