Do What You Love

Q&A with Michael Xiao, head of Data Science and Analytics at Clearcover Interview by Rolande Mbatchou Odeniyi

Photo: Shutterstock.com/tomertu

Michael Xiao
Michael Xiao

Why did you decide to become an actuary?

The story of me becoming an actuary is far more interesting than the “why.” When I was in college, I discovered the profession when my mother read an article about it being the No. 1 job in America and suggested that I look into it. I also seriously considered management consulting but decided the amount of time spent on planes and in hotels wasn’t for me.

In college, I majored in film and spent most of my time on film-related activities, such as founding and editing a film journal and creating film programming for a local arts center. During my senior year, I wrote a feature-length screenplay with the intention of shooting it. My professor, who had some professional screenwriting credits, loved it, so I decided to take a risk and go make the movie on a shoestring budget.

At the same time, I’m fairly practical and realized there was more than a fleeting chance that I wouldn’t make the next award-worthy movie. I had done some research my senior year and realized that the actuarial profession combined a good mix of business, applied math and computer skills, which appealed to my broad range of interests. I took a couple of actuarial exams and passed.

There’s a reason that movies often require million-dollar budgets and tens, if not hundreds, of people collaborating—and even then there’s no guarantee of success. In the course of editing my film, I realized it wasn’t going to be the launching point for my directorial career. I applied for actuarial jobs and landed in the development and rotational program at a large health insurer.

What major career moves got you to where you are today?

I believe the path to becoming a successful executive requires a deep understanding of how companies, people and organizations run, and the ability to effectively apply that knowledge. Some of that knowledge is business understanding, which actuaries naturally develop in insurance if they take on different actuarial roles, and some of that is broader management and leadership skills, which can either come naturally or be trained. Moving to different parts of the business, working with different groups of people and taking nontraditional roles can accelerate both.

For me, it’s been about taking risks with new roles based on their potential and not just whether it’s an immediate step up. There was one pivotal move I made, some of which was based on insight and, frankly, a lot of which was luck. Actuarial and statistical techniques are great for population-level analyses and decisions, but I realized there was significant room for improvement when it came to making predictions at the individual level, whether claims or the customer level.

So, back in 2012, when I was close to wrapping up my actuarial exams, I started studying machine learning. By chance, my employer started a new data science organization in 2014, and I was able to quickly transition over since it was still the Wild West of data science and machine learning (today, it’s much more mature). I moved from an actuarial managerial position to an individual contributor leading a team of data scientists and engineers, but I believed the opportunity was tremendous and there would always be actuarial roles available for FSAs. Basically, it was a reversible decision if I failed.

I’m where I am today because that move turned out to be a great one. Now, whenever I’m being considered for a leadership position that involves data science, few candidates have more practical and leadership experience than I do.

Why have many of your career moves been in nonactuarial roles?

The primary reason has always been the fact that I have the interest. Many actuaries are perfectly happy in traditional actuarial roles, and if that’s you, more power to you. Don’t change a thing. I’ve always wanted to do and learn things outside of the actuarial world. The training and knowledge I gained as an actuary will always be tremendously valuable, especially in the insurance world.

What are some of the major challenges of leading a technical department/division?

There are general leadership challenges and then there are ones specifically for a technical department and division. If you’re leading a large technical organization, any time you spend doing technical work—and at a senior level, even reviewing technical work—is destroying value for your employer. If you’ve hired correctly, members of your team will be able to do that work far more effectively.

Often, actuaries are promoted based on their technical competency, which means that they probably enjoy doing technical work. So, the first challenge is being able to step away from the technical work. The second challenge is that you still need to stay up to date on what’s going on technically, without doing the work, or your team won’t respect your decisions.

Then there’s the general leadership and management side of things. A principle I strongly believe is that as a leader in a large organization, you should act as a multiplier. Making your employees 10 percent to 20 percent more effective justifies your role. The things a leader of a department should focus on naturally flow from that principle.

There are also things that a more senior leader can do far more effectively than others. Some examples, not meant to be exhaustive by any means, include identifying gaps in and effectively structuring your organization (generally less of a problem for mature actuarial organizations compared to new and growing organizations like data and analytics organizations); creating a shared vision for your organization, so everyone can move in unison toward it; coordinating and collaborating with other executives to get buy-in and help achieve company goals (this is a cost at larger companies, but an unavoidable one); advocating and retaining your highest-performing team members; and focusing a lot of attention on high-cost, nonreversible decisions.

How can an actuary negotiate to get senior-level roles?

Negotiation alone will not get you a senior-level role. First, you must have the right background and experience for the role. The more diverse your background and experiences, the greater your chances of getting something more senior. The reality is, you also must look both within and outside of your current employer. Sometimes the right opportunities won’t be there internally and your management won’t have the power and ability to move you into a senior role, no matter how much they believe in you. This seems to be especially true at larger companies, where the amount of red tape can be troublesome. Don’t take that personally.

A piece of practical advice would be to learn interviewing skills, which deliver oversized returns. I’ve interviewed hundreds, possibly even more than 1,000 people, and it’s amazing how often really smart people can’t concisely and effectively communicate their achievements.

If someone hasn’t worked with you extensively, don’t expect them to know anything about what you’ve done. This is a skill that’s useful even outside of job hunting when you must convince nontechnical stakeholders of the value of your team and why they should invest more resources into your organization versus another.

What advice do you have for a young, ambitious actuarial student?

This advice might be a cliché, but do what you love. Look inside of yourself and identify what it is you most want to do at work and ask yourself how to get there. If you can’t answer that question, do a little soul-searching. Whenever someone comes to me for career advice, I tell them I can’t decide what they want to be for them, but that I can give them advice on how to get there if they do know.

What are some of the major challenges facing actuaries today?

A realization I had coming out of a Society of Actuaries (SOA) session on the impact of artificial intelligence (AI) is that actuaries can’t be both data scientists and actuaries. The skill sets are actually different in some key aspects, even if on the surface they appear very similar.

Michael Xiao is head of Data Science and Analytics at Clearcover.
Rolande S. Mbatchou Odeniyi, ASA, MAAA, is managing actuary, Provider & Network Data Science, at Health Care Service Corporation. She is also a contributing editor for The Actuary.

Statements of fact and opinions expressed herein are those of the individual authors and are not necessarily those of the Society of Actuaries or the respective authors’ employers.

Copyright © 2021 by the Society of Actuaries, Chicago, Illinois.