Grow Past Your Weaknesses - Commencement Speech to Stanford Class of 2019 in Mathematics, Statistics, and Mathematical & Computational Science

This weekend, I had the distinct honor of addressing graduates from the Stanford Class of 2019 at a joint ceremony for the Mathematical and Computational Science (MCS) program, the Mathematics department and the Statistics department. As an added bonus, I was introduced by Statistics Department Chair Art Owen, who was my thesis advisor during my own time at Stanford.

Below are my remarks. Congratulations again to the graduates of 2019!

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Thank you, Professor Art Owen. What an honor to be here, back on the graduation stage. A full circle since I graduated in 2010.

First, I have a quick confession: over the last week I kept hearing stories about how excited you all were to have a well-known tech industry leader addressing the graduating class. I was very flattered. Then I arrived on campus this morning, and someone said to me: “Hurry up, or you’re going to miss Tim Cook’s speech!” …so I’m very thankful to all of you for sticking around.

When I accepted the invite, I also thought it was common practice to give the commencement speaker an honorary degree. After all, Harvard gave one to Oprah Winfrey. They even gave one to Bill Gates and he didn’t finish college. I get it. I already have one from the Statistics Department, but it would have been nice to add to my collection Doctor of Mathematics. I feel better knowing that Tim Cook isn’t getting one today, either.

Apparently, here at Stanford, we don’t give out honorary degrees. I guess we all have to earn it the hard way. Congratulations, graduates of 2019! You should be proud! You now hold a degree even Oprah Winfrey cannot get! I’d also like to acknowledge the families and friends who have supported you all along the way, especially the parents and all of the loved ones here in the audience.

I also need to thank my primary speechwriters, my two boys Leray and Tavi. When they first offered to help me, I was skeptical. How much can a future Stanford graduate do when they are only 6 and 4 years old? But I think I got my money’s worth. If anyone in the audience has complaints about the quality of this speech, please talk to them afterwards.

It is indeed a wonderful achievement, sitting where you sit. I know from my own experience it is not easy. But seriously though, who came up with the idea to give the students a qualifying exam after they were already admitted to the program? After I survived that first year summer, I came to the conclusion that the qualifying exam wasn’t just there to prepare me for a PhD. I was qualified to handle whatever life would throw at me after that, including professor Art Owen, my thesis advisor.

Thank you, Art! I truly enjoyed working with you. Happy Father’s Day to you and to all the dads who are here with us today.

After I was invited to give the speech, I thought hard about what to talk about. The first thing that came to mind was to give you some advice on job search. After all, I do work at LinkedIn, and there might be some parents out there who are worried that if you don’t find a job, they’ll have to listen to you talking about set theory at their dinner table for who knows how long.

But then I remembered whom I’m talking to. There is no better time to be you! With the rise of AI, demand for your skillset is higher than ever. And of course, the Stanford brand doesn’t hurt. So, I think you’ll do just fine in your job search. If not, you can always try looking on LinkedIn.

But getting a job is just the beginning. The trajectory you are on extends far beyond the diploma you’re receiving today. As a Stanford graduate, I’m confident that you’ll all thrive in your first position.

The question is, what happens after that? Working at LinkedIn, I have access to one of the world’s most comprehensive datasets on career paths, and I can say, for the 200 of you graduating today, this is what is likely going to happen to you over the next 5 years:

• On one end of the spectrum, we have the lucky 5% of you who will be getting a promotion every year;
• On the other end of the spectrum, there are 20% of you who will still be stuck in the same position at the same company 5 years from now.
• Many of you will switch companies, but overall, only 30% of you will have any noticeable progression in seniority.

Of course, “past performance is not an indicator of future results" as they say in finance. So, how do you avoid this regression to the mean? What will get you into that next standard deviation in the bell curve?

In the last few years, many of you have focused on your strengths—like math and statistics. And that devotion has paid off: with a diploma today, and jobs lining up for tomorrow. All because you are great at what you do.

What I have found is that in the long term, it’s not just your strengths, but your weaknesses, that will determine how far you can go.

Let me share a story from my first job after Stanford: When I graduated, I took my passion for statistics with me to Microsoft. Three months into my job, I was asked to join a technical discussion about browser cookies. Unlike my kids, I had no interest in cookies, not how they are made, not how they are stored, or the engineering details that came with that. I remember thinking about how I’d much rather go back to my desk and deal with statistical distributions and convergence theories than stay in that boring meeting. After all, that’s what I was really good at, and that’s what I got my PhD in!

Shortly after that meeting, a colleague came to me and said: Ya, I know the engineering details are not your domain, but what good is your statistics expertise if you are not equally an expert in the domain your statistics is applied to?

That candid conversation was a turning point. I started to realize that what was holding me back from solving the really important problems wasn’t because I could be better at proving convergence theorems. It was because I could be better at many other things, such as turning these theorems into working engineering solutions, and communicating these theorems to the 90% of people I work with who don’t know what a p-value is.

But having that realization is one thing; working on it is another. It can be tough to face your own weaknesses. For me, the biggest hurdle was the imposter syndrome, or the fear of being seen as incapable.

That’s why the first thing I had to conquer was learning to be vulnerable, that it is ok to not only have weaknesses but for others to know I have weaknesses. Growing up with the belief that I should always try to tackle things on my own, I found that opening myself up wasn’t easy. But it is not just me. The number one reason people don’t speak up in groups is because they are afraid of saying something that may make them look stupid. On the other hand, the number one mistake new managers make is to assume they are smarter than their team at everything. The reality is that except for your own parents, nobody thinks you are perfect anyway. You might as well show them the complete picture of who you are. Being vulnerable also gives others permission to offer you their help. Pro-tip: the more help you get, the less likely you are going to look stupid the next time.

The second thing I had to work on was learning how to ask for help. You may say: “of course I know how to get help!” You get help all the time, from your professors, your TAs and your RAs. Isn’t that what you do as students? That is right. You have been getting help from people whose job is to help you, and in a structured environment that is designed to help you. Now imagine you are hired because you are one of the best, a domain expert in your field. All of a sudden, it can feel a lot harder to ask for help. If you thought going from structured data to unstructured data was tough, now you are going from structured learning to unstructured learning. No one is going to check your problem sets or hold office hours just to answer your questions. It is going to be much more important to take initiative, to build a strong support network and to find trusted work-spouses. The best thing I’ve done was to find a good mentor. But don’t bother getting a mentor unless you are ready to be vulnerable.

Finally, and most importantly, you must believe you can achieve anything you set your mind to, including overcoming your weaknesses. Whenever I think about believing in myself, I think about my mom.

My mom is this petite woman, only 4 feet tall, and didn’t even finish elementary school. On the surface, she may seem to be powerless yet she’s the most powerful person I’ve ever met, all because of her devotion to her belief. When I was born a long, long time ago, in rural China, nobody wanted girls. My mom not only had a girl, she had two. Everyone had something negative to say about it, including my own grandparents. But my mom believed differently. She believed in my sister and me. She believed that girls can be as good as boys. To prove everyone wrong, she worked day and night to pull my family out of poverty so she could provide us better things and opportunities. She biked us 10 miles every day to the school in the city so that we could have a better education. And she did it. She proved them all wrong. My sister was the first in my extended family to go to college. And I think I turned out okay, too.

My mom had a belief, and it took her years, but she achieved it. While she has taught me many things, this lesson has inspired me the most. So, as you set out to remove the barriers holding you back, connect with your inner source of inspiration. Step by step, you too will realize you can achieve anything you put your mind to.

Today, we are celebrating a great achievement and the beginning of a new chapter in your life story. In my own story, I went from being a statistician who didn’t care about cookies to becoming someone who can actually speak the language of both Statistics and Engineering. This in turn led me to become the leader for experimentation and then all of Data Science at LinkedIn.

While you should all take pride in the many strengths that have carried you to where you are today, I’d encourage you to be honest about your weaknesses, and not be bound by them. The ultimate confidence is when you are confident about what you are not good at. Get help and draw strength from people around you. And while it can seem scary at first, always believe. If I can consider myself as a statistically significant sample—even with N equals 1—then I’d say that it will serve you well. Good luck elevating your career into the next standard deviation!

Thank you.