A user manual to operating Eugene Yan. A work in progress, just like me.
A short intro
- I’m from Singapore; spent most of my life and met my wife there. Now in Seattle.
- I’m an introvert by nature and spend my weekends mostly at home. Nonetheless, work and public speaking has trained me to be a pseudo-extrovert.
- Started in investment policy, then transitioned to data science.
My experience so far
- Investment Analysis @ Ministry of Trade and Industry, Singapore
- Data Science @ IBM (Supply chain, anti-fraud, workforce analytics)
- Data Science @ Lazada, an e-commerce start-up; acquired by Alibaba
- Data Science @ uCare.ai, a healthtech start-up
- Applied Science @ Amazon (current)
What do I value most?
- Growth: Continuous learning via working on challenges at the edge of my abilities.
- Creation: Building machine learning systems & teams, through code & leadership.
- Service: Working to improve lives, and leave things better than I found them.
- Autonomy: Freedom to figure out the best way to approach problems, life, etc.
- Connection: To engage with people I admire for mutual growth and inspiration.
- Experience: To enjoy life through travel, food, reading, with loved ones.
What are my quirks?
- Chronic Imposter Syndrome: I’m surrounded by people much better than me; the Internet makes this easy. Thus, I never feel good enough (and value Growth).
- I find faces distracting: When we talk, I’ll often be staring somewhere above your head—this is how I focus. Please don’t be offended.
- I like to joke and kid a lot: If I’m poking fun at you, it means I’m close to you and trust you can take it. But do let me know if I should stop.
- I can be too direct in discussion: Some view this as confidence, some view it as being confrontational. Actively working on this.
What do I enjoy working on?
- Shipping data & ML systems (end-to-end) to serve customers and deliver results.
- Engaging with business to define (the right) problems, deliverables, and outcomes.
- Building high-performing teams & mentoring practitioners to grow the industry.
- Writing & speaking about how to be effective in data science and machine learning.
How do I prefer to work?
- Starting with Intent (What’s the goal?), Deliverable (What should a solution look like?), and Boundaries (What can I not do? Having boundaries provides more freedom than without boundaries).
- My energy and focus is highest early in the morning (8 am), and wanes past 3 - 4 pm. Thus, I prefer Deep Work at this time, and meetings after. Brain-dead at 6 pm.
- I prefer running some analysis or building a prototype before sharing my ideas—they seem so outlandish to me that I rather test them before wasting your time.
- I enjoy working end-to-end: This means everything from “Defining the Problem”, to “Deploying the Solution”, to “Measuring the Results”. This lets me iterate & ship quickly. I’m generally aligned with these approaches by Stitch Fix and Netflix.
- I prefer to Ship Early, Ship Often: One A/B test every 2 weeks = 26 lessons a year. Not shipping after 3 - 6 months is probably too slow for me.
- Definition of Done: The system should be deployed and the impact measurable.
How am I like to work with?
- I’m not always on email or messenger. I usually check once before lunch, and once before end of day. If you need me, don’t hesitate to
@eugeneyan or call on the phone.
- I default to openness and complete trust—it’s just easier to work this way.
- A good leader only needs to do 3 things: Provide (training, motivation, resources, opportunities, etc.), remove (blockers, confusion, politics) and get out of the way.
- What makes a good leader? I like a16z’s definition: Vision (Steve Jobs), Caring for people (Bill Campbell), Execution ability (Andy Grove)—at least two out of three.
How do I prefer to communicate and get feedback?
- 2-minutes: I might ask you for 2-minutes to bounce an idea off you, or to rubber duck. 2-minutes is usually 10 - 30 minutes. 15-minutes = “We have a problem.”
- Face-to-face: Writing just doesn’t convey the message well enough, the facial expressions and tone matter.
- Feedback: I enjoy feedback early and often. My default qns - “What should I do more of? What should I do less of/stop doing? What can I improve on?”
- Crocker’s Law: I believe feedback is a gift and will not take offence; I don’t need the shit sandwich around it.
- When giving others feedback, I prefer to give it in a private, casual setting, preferably 1-on-1.
- Empathy: I care deeply about doing the right thing for customers and the team.
- Extreme ownership: I cannot help but act like an owner; nothing is not my job.
- Bias for action + Delivering results: I iterate & ship fast, and measure results.
- Pragmatism + Simplicity: I design the simplest solution to complex problems.
- Communication: I’ve been told that I write & speak better than most tech folks.
What are my weaknesses? (mirrors my superpowers)
- To iterate fast, I’m okay with lowering standards in the short-term and taking on minor tech debt (which I pay off after shipping).
- My enthusiasm wanes when working on things that aren’t meaningful, or actively harm people; important to start with a meaningful Why? (i.e., Intent)
- I’ve received feedback that I need to show more “science depth” by publishing research papers (like PhDs); trying to do this after each big project shipped.
What do I not have patience for?
- Politics: Backstabbing, putting people down, stealing credit, malicious gossip, etc.
“We are what we repeatedly do. Excellence, then, is not an act, but a habit.” - Aristotle (and Will Durant)
“If you are not embarrassed by the first version of your product, you’ve launched too late.” - Reid Hoffman (interpreted as “Ship Early, Ship Often”)
“Failure is an option here. If things are not failing, you’re not innovating.” - Elon Musk
“The number one predictor of success for a very young startup: rate of iteration.” - Sam Altman
“The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” - Alvin Toffler