不是理科PHD还是别转了 另外DS面试现在已经妖魔化了 转码只要刷leetcode 转DS要刷leetcode和这些 According to interviews and Linkedin, Data Scientist should: 1. Write a software engineer-level production code. 2. Be an expert in advanced level statistics. 3. Have a history of writing Python packages and APIs. 4. Being able to recall everything about time series, computer vision, signal processing, and natural language processing on demand. 5. Have ideal GitHub with pages of done APIs and perfect Read Mes. 6. Expert in SQL, Hive and Kafka. 7. Being able to build a data warehouse from scratch. 8. Extensive knowledge in Data Architecture 9. Extensive knowledge in Data Engineering 10. At least 5 years of experience being a Product manager 11. Azure and AWS certifications 12. Being able to build and maintain ML pipelines 13. Excellent Tableau and Power BI visualization and administration skills. Must also pull all data in SQL and manipulate it before plugging it into the platform. 14. Have top Secret Clearance 15. Must be okay with the Data Analyst title and work for 50hr on 1099. 16. Must be able to lead a team of Data Scientists for an entry-level positing in DS. 转自linkedin恶搞贴
re,我火坑专业,转了ds。现在觉得还不如不转,ds是个更大的坑。要转就转硬核一点的吧,比如software engineer, data engineer。
+1. 太对了
这个方向都处在烧钱的阶段,真正有用的产品很少,有商业效益的产品就更少了。中看不中用。现在这么热因为大家都还在消费这个potential,等看清了potential只是potential,泡沫就要破了。要转就转硬核一点的吧。
一样火坑专业的,我开始预选课,打算学B超。你知道physician assistant 是不是对语言要求更高? 但相对更加好找工作?
我以前一个lab的小师妹,读博的时候修了个统计master,现在在facetime做DS,我很佩服
跳坑有不同的路线,要找最适合自己的。。。
妹子现在工作怎么样?
这个np 和pa不需要先读社区大学的rn program吗?也得三年啊……
我本科学医的朋友基本上不用再补什么课,本科生物的都是工作的时候补的课,直接申请。。。
According to interviews and Linkedin, Data Scientist should:
1. Write a software engineer-level production code. 2. Be an expert in advanced level statistics. 3. Have a history of writing Python packages and APIs. 4. Being able to recall everything about time series, computer vision, signal processing, and natural language processing on demand. 5. Have ideal GitHub with pages of done APIs and perfect Read Mes. 6. Expert in SQL, Hive and Kafka. 7. Being able to build a data warehouse from scratch. 8. Extensive knowledge in Data Architecture 9. Extensive knowledge in Data Engineering 10. At least 5 years of experience being a Product manager 11. Azure and AWS certifications 12. Being able to build and maintain ML pipelines 13. Excellent Tableau and Power BI visualization and administration skills. Must also pull all data in SQL and manipulate it before plugging it into the platform. 14. Have top Secret Clearance 15. Must be okay with the Data Analyst title and work for 50hr on 1099. 16. Must be able to lead a team of Data Scientists for an entry-level positing in DS.
转自linkedin恶搞贴
属实。
https://www.mitbbs.com/article_t/Programming/31577079.html
我一直往云方向转
统计的还是去药厂吧。
最难的是上岸,运气占大头。之后修行看个人。。 如果你是dry lab估计容易一些,每天晚上娃睡了准备三四个小时,三四个月后就开始海投简历吧,投出去也不一定马上面。另外得有耐心,一年不出坑也算正常。比较hands on的话转码也可以考虑。 给你个认识的dp,late 30,17投简历,18上岸,疫情期间跳槽,tc > 30w