https://eugeneyan.com/rss 09月30日
刘宇安与科学写作
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刘宇安,一位从政策分析师到数据科学家的职业转型者,现为亚马逊应用科学家,利用客户行为数据帮助推荐产品。他因擅长写作而闻名,其个人网站eugeneyan.com涵盖机器学习、职业发展等主题,通过写作实现个人成长并吸引志同道合者。从新加坡到美国,他的职业生涯始终围绕帮助他人展开,从IBM到Lazada再到亚马逊,每一次转变都体现了这一核心动机。写作不仅是他的爱好,更是他深化理解、建立联系的重要工具,尤其在注重写作文化的亚马逊,他的文档撰写能力得到高度认可。

📚 刘宇安的职业轨迹充满转折,从政策分析师到数据科学家,再到亚马逊的应用科学家,但他始终不变的动机是帮助他人。他利用客户行为数据帮助推荐产品,并在职业生涯中不断学习与成长。

💡 他创办的个人网站eugeneyan.com始于个人发展需求,后因分享内容吸引大量读者,成为他深化专业知识、建立人脉的重要平台。写作帮助他学习更好,并吸引了志同道合的朋友。

🧠 刘宇安强调沟通能力的重要性,尤其在数据科学领域。他通过写作实践提升了表达能力,并认识到清晰的文档撰写能力在亚马逊等注重写作文化的公司中的价值。

🌐 他的写作理念是‘为自己写作’,而非追求社交效果。他认为通过持续写作可以找到自己的声音和受众,并建议 aspiring writers 从实践开始,逐步找到自己的方向。

Originally published on Amazon Science.

Eugene Yan’s career path has taken some unusual turns, but his motivation has always been the same: understanding people so he can help them. A policy analyst turned data scientist, Yan is now an applied scientist at Amazon using customer-behavior data to help recommend the best products. In the world of machine learning, however, he’s best known for the way he writes it all down. On his personal site, Yan covers a range of professional and technical topics like machine learning systems, data science methodology, dealing with imposter syndrome, and building data science teams.

Eugene Yan started eugeneyan.com in 2020, focusing on general machine learning and career content. Initially it was for personal development, but then people started reading, and now writing posts takes up the majority of his leisure time.He started the site for personal development, but then people started reading, his network started expanding, and now writing posts takes up the majority of his leisure time. “It snowballed,” he said. “Writing helps me learn better. And when I share it online, it attracts like-minded readers and helps me make new friends. ”

Born in Singapore, Yan studied psychology at Singapore Management University. “I was curious about people, how they perceive, and how they behave,” he said. His college research focused on how competition affects people differently, motivating some and intimidating others. After college, he joined the Singapore government as a policy analyst sifting through legal cases and trade agreements. But it wasn’t long before he began to miss crunching numbers and following the data on human behavior. “I envied my colleagues in commodities who used on numbers and worked with spreadsheets,” Yan said.

He decided to try and make the switch to a data science position based on some familiarity with the subject from his undergraduate research days. He landed a position at IBM in 2013, and from there he moved to data science roles at Lazada, a Southeast Asian e-commerce site, and then UCARE.AI, a healthcare startup.

A desire to help

“In every change in my career, what drives me is helping people,” Yan noted.

At IBM, it was helping people find new roles. At Lazada, it involved helping people find products they need. At UCARE.AI, it entailed predicting chronic diseases and preventing high insurance payouts. “This brings me more satisfaction than dollars and cents,” he said.

While at Lazada, Yan decided he needed more training in the fundamentals and pursued a master’s in computer science from the Georgia Institute of Technology. He graduated in 2019, and then he and his wife began considering a move overseas. He applied for a position at Amazon, drawn to the company’s leadership principles and the ability to help customers read more. He relocated to Seattle to join Amazon in 2020.

While Amazon has several ways to help readers find books, from Amazon Book Review to Amazon Charts, Yan is part of a team developing the recommendation systems that power the widgets behind the Amazon Store’s personalized book suggestions. “Customers tell us what they like based on what they do,” he explained. “They browse for a specific book, a genre or a topic.” His team uses those signals to help surface additional books a reader might like. Ultimately, Yan and his team want to make reading easier.

Writing it all down

Early in his transition to data science, Yan started interviewing mentors for advice, some of whom were “rock star data scientists.” He asked what skills he should cultivate to be successful. The one skill a majority of mentors suggested was communication. The people he spoke with emphasized how communication becomes more and more important as you rise in the ranks. “I was like, ‘Are you kidding me?’ But more and more mentors said the same thing,” he recalls. “I thought, ‘This can’t be right, but I’m just going to try it.’”

Yan started practicing his writing, first publishing to a WordPress site. He wrote dozens of posts unnoticed, but then in 2020 created eugeneyan.com and started writing more general machine learning and career content. His writing began to gain an audience. Posts like “Unpopular opinion — Data scientists should be more end-to-end” received more than 500 likes on Twitter. One post on note-taking received 35,000 unique views in a single day. Feedback and praise began to pour in, and his “practice” website swelled into something much bigger.

For a brief period, Yan tried to sustain this level of social engagement. He wrote to please a mass audience and get clicks. “That quickly became unfulfilling,” he said. Now he focuses his writing on topics he wants to learn and aims for an audience of people he’d hope to be friends or colleagues with. “I might have fewer readers now since I’m choosing more technical topics, but these readers comment, disagree, and email me. Each comment and real relationship are worth more than 10,000 likes,” he said.

The many benefits of good writing

Yan’s decision to become a better communicator and writer is especially valuable at Amazon. “The writing culture is rigorous at Amazon,” he said.

Amazon’s working backward method starts with an individual or team imagining the product or service is ready to launch. The individual or team’s first step is to draft a press release announcing the product’s availability, and explaining its significance. Moreover, meetings often start with participants reading a six-page document about the meeting’s topic before discussion begins.

Finding your voice and niche doesn’t happen overnight — you have to write and share your work. So just start somewhere, anywhere, and keep writing. — Eugene Yan

“I write as many documents as I code,” Yan said. Recently he received feedback that one of his design documents was easy to understand and clearly laid out everything the reader needed to know. In this way, his writing skills complement his design and machine learning skills. He also started a new site, Applying ML, which includes interviews with machine learning practitioners.

Yan is often asked by aspiring writers for advice on how they can improve their skills. The number one piece of direction he offers is to write for yourself — what do you want to learn and clarify your thinking on? — rather than social engagement. The second piece of advice: “just write.” The best way to figure out your niche and your audience is to simply put fingers to keyboard and start practicing, he said. Maybe after a dozen — or a few dozen — pieces you find your voice, what you want to write about, or what resonates best with the people reading along.

“If you never start writing, how will you know? Just like Blue Origin’s motto ‘Gradatim Ferociter’, which means ‘Step by step, ferociously’. Finding your voice and niche doesn’t happen overnight — you have to write and share your work,” he said. “So just start somewhere, anywhere, and keep writing.”

If you found this useful, please cite this write-up as:

Yan, Ziyou. (Aug 2021). Amazon Science - Eugene Yan and the Art of Writing about Science. eugeneyan.com. https://eugeneyan.com/speaking/amazon-science-feature/.

or

@article{yan2021science,  title   = {Amazon Science - Eugene Yan and the Art of Writing about Science},  author  = {Yan, Ziyou},  journal = {eugeneyan.com},  year    = {2021},  month   = {Aug},  url     = {https://eugeneyan.com/speaking/amazon-science-feature/}}
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刘宇安 科学写作 数据科学 亚马逊 职业生涯
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