Onboarding as a Machine Learning Engineer

It’s been 3 months since I started my new position as a Machine Learning Engineer (MLE) at Spotify. What I like most about this position is that I get to participate in building an end-to-end pipeline, including ideation and experiment, data engineering, machine learning modeling, model serving, online A/B test, monitoring, and many more. 

Tips for first-time mentors from a first-time mentor

This summer, I volunteered to be a mentor for a data science intern. It reminds me of my own internship 2 years ago, when I learned so much from my mentor (see my previous posts). Being a mentor not only allows me to view a summer internship from the other side of the table, but also presents new challenges and learning opportunities for myself. In this post, I will share some tips for first-time mentors from my experience as a first-time mentor. 

How to nail a presentation

Now that we have done most of the hard work: numerous experiments, survey, coding, refactoring, pipelining, analysis, visualization, charts, numbers, written documents and so on, we are going to give a final presentation. “That’s easy,” one may think, “Just paste my results into PowerPoint slides and click through it.”

Having seen quite a lot of presentations at conferences, group meetings, and tech demos, and having given many presentations myself in different scenarios, one thing I can say for sure about presentations is that “It is not easy” at all. It is as demanding as most of the hard work we have done, and requires similar learning and practice as coding, analysis, and writing. In this post, I will summarize what I learned from my mentors, teachers, peers, as well as my own mistakes about presentations.

北美博士的咨询申请之路

consulting yes or no or maybe?

声明:本文作者最近也开设了个人博客(https://yaqiongchen.com/),如有问题和评论,请直接进入原作者的博客 北美博士的咨询申请之路。这里的评论已关。

这篇稿子应博主Ju的邀约而写,主要是总结一下北美博士找咨询工作的经验和教训。我的背景是国内Top2本科,哥大生物专业博士,下个月入职一家咨询公司的New York Office。在求职期间得到了很多的帮助,希望也能尽一份自己的绵薄之力,帮到更多的后来人。

DIY curriculum for post-school life

post-school

Last February, I defended my PhD thesis and graduated from more than 2 decades of school life. Now, it’s been a full year of post-school life. There are no more exams and curriculum to quantify my GPA. In this post-school life, I start to realize that I have to be the one setting my own goal, designing my own curriculum, and evaluating my progress introspectively. In this post, I am sharing some lessons that I find useful in DIY curriculum. 

Do you write production code as a data scientist?

production

In the past month, I posted this question to my friends, peers, online tech forum, and got responses from more than 30 data scientists in various industries and different academic background and career path. The responses show a wide spectrum of data scientists’ involvement in production, and reveal some shared concerns about career development among data scientists.

Not ready yet…Go!

I officially graduated from Columbia last Tuesday after my PhD thesis defense, and started to work full time immediately in the following week. This is the first week of my transition from academia to industry, and I already experience some culture shock in time management and prioritizing. Learning on the job is not only about the technical details, but also about the pattern of thinking.