Eugene Yan

Hi, I'm Eugene Yan. I design, build, and operate machine learning systems that serve customers at scale. I also write and speak about data science, data/ML systems, and career.

Currently, I'm an Applied Scientist at Amazon shipping ML and recommender systems to help customers read more.

In the past, I led the data science team at Lazada (acquired by Alibaba in 2016). Personally, I shipped the ranking system (conversion & revenue up 5-20%), smart push-notifications (CTR & add-to-cart up 10%), and automated product & review classification (cost down 90%). Hypergrowth's fun =)

As early hire in a healthtech Series A, I led the team to ship a ML system for Southeast Asia's largest healthcare provider. At IBM, I built job demand forecasts & recommendations.

My work focuses on applying machine learning to serve users at scale, from workforce analytics, healthcare disease and cost prediction, to e-commerce recommendations and automation. You can learn more via my talks and writing.

Need advice on your company's data/ML or team challenges?  Here's how I can help. Send an email or schedule some time; if your qn can help others, please use this AMA.

Timeline

2020-now: Applied Scientist @ Amazon

(RecSys, ML Systems)


2018-2019: Data Science Lead @ uCare.ai (Disease Detection, Resource Allocation)


2017-2018: VP, Data Science @ Lazada (Alibaba) (E-commerce ML Systems)


2015-2017: Data Scientist @ Lazada (Alibaba) (Ranking, ML Automation)


2013-2015: Data Scientist @ IBM (Workforce Analytics)


2011-2013: Investment Analyst @ Ministry of Trade & Industry (Analysis, Negotiation)

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Bio

Eugene Yan designs, builds, and operates machine learning systems that serve customers at scale. He's currently an Applied Scientist at Amazon. Previously, he led the data science teams at Lazada (acquired by Alibaba) and uCare.ai. He writes & speaks about data science, data/ML systems, and career growth at eugeneyan.com and tweets at @eugeneyan.

Images: 960 x 960, 738 x 738, 200 x 200


FAQ

Why do you write?

I enjoy sharing my experiences and what I’ve learned, so others can avoid my mistakes and build on my lessons. I’ve been fortunate to work in awesome teams to solve challenging data & ML problems and ship to customers worldwide. Here, I hope to share some lessons and perspectives, with a pragmatic and product slant.

Also, as I continue to explore and learn, writing helps me to learn better. And when I share my thoughts and writing online, they attract like-minded people with whom I can discuss with and learn from. Read something that you would like to share, ask, or discuss about? Tweet me at @eugeneyan or reach out via email.

What do you write about?

I’ll write about what I’ve learned or thought about. It’s usually related to the topics of data science, ML in production, or career. Here’s a word cloud based on the 55 posts I wrote in 2020. We can see common themes in (i) data & ML, (ii) problem & product & user & people (iii) writing & coding & learning.

Wordcloud of my 55 posts in 2020

Sometimes, I also write to answer questions I get from readers. This includes questions about my productivity habits, why read papers, the importance of writing for tech roles, and the difference between data/ML roles.

There will also be writing that might not be related to data science or ML. This includes topics on Commando, Soldier, Police, Beginner’s mind, and the 85% rule. Nonetheless, I hope you’ll also find them valuable.

Truth be told, I’m still figuring it out. Don’t be surprised if I write about completely different topics in future. If you want to keep in touch, subscribe to my newsletter.

Who do you write for?

I mainly write for two individuals and a group.

The first person I write for is myself. I try to write things that, when I revisit in a year or two, are (still) interesting; hopefully, this makes it useful for others too.

The second person I write for is my wife. She's always the first reader of my drafts (at least, until she gets sick of it). If she can understand what I write, especially on some of the more technical topics, mission accomplished.

The group of people I write for is my previous, current, and future teams. I pen my views on machine learning in production, data science & agile, and end-to-end data science, etc. This way, when the need arises, I've thought through them.

How can I get in touch?

Email's the best way. Else, try Twitter or LinkedIn. More details in the footer below.

How's your 2021 goals been?
  • 48 posts: 31 / 48
  • 4 talks: 8 / 4
  • 100 “this is awesome/helpful”: 100 / 100
  • 3-6 mentees achieving the next level: 2 / 3
  • 1-3 start-ups invested in/advising: 1 / 1
  • Meditate 60 minutes daily: 268 / 365
  • Learn to snowboard: 0 / 1
  • Learn TypeScript: 0.5 / 1 (learning-typescript, applyingml)
  • Eat out twice a month: 7 / 12
  • Read 6 fiction/pseudo-fiction books: 0 / 6 (Suggestions)
  • Visit 3 US states: 1 / 3 (Los Angeles)