Degree from Michigan: B.S. in Math and BBA

Current location: San Francisco, CA

Year graduated: 2013

Student orgs involved in at Michigan: MPowered Entrepreneurship, Math Club, Delta Sigma Pi, and Student Budget Advisory Committee to Provost

Other jobs held or graduate programs attended since graduation: Business Analytics Associate at ZS Associates; Data Science Fellow at Zipfian Academy



HZ: I am a data scientist with Tesla working with the reliability engineering group. We are trying to change how people use transportation, focusing both on autonomy and on bringing about renewable energy as the main energy source behind vehicle transportation. A lot of what we’re doing right now is making attractive vehicles so people will consider replacing their gas-consumption vehicles with electric vehicles.


KC: Tell me more about Tesla’s reliability engineering group!


HZ: People see a Tesla and say, “Ooh, fancy car!” but we like to think of it as a computer with wheels. Think about a computer; it’s something that you replace every 4 or 5 years, mostly because every couple of years, there are leaps and bounds of improvements made in the hardware for computers. However, with cars people aren’t thinking about getting a new car every 4-5 years; they’re thinking more along the lines of every 10-12 years. We need to build these cars with the mentality that they’re going to last like a traditional car but technically function more like a computer.


With the reliability engineering group, our goal is to bring that car to that 12-year mark. We want to build something that’s durable and can last the elements that most people expect their cars to withstand. We try to bring together design, engineering, service, and manufacturing teams to think of the longevity of the vehicle, as opposed to what it is just out the gate.


There are a lot of details to our work, but the most exciting part that we’re working towards is autonomy. Most people think their car is going to last 100,000-150,000 miles, but you have to take into account that for the majority of the day, your car is sitting in a parking lot and not being used. We’re moving towards a future where cars are fully servicing; they will go places picking people up, so you might be sharing a vehicle with someone who has an entirely different schedule from you and doesn't maximize the utility of the car. So now, perhaps the car is able to survive 500,000 miles over the course of its life. We’re designing towards that future to address overutilization, which is the case now.


KC: Are cars the main focus of Tesla’s business?


HZ: The other side of Tesla’s business is its energy business – if anything, this is even more interesting for Tesla’s future. Think about how energy works currently; we have wires running underground and overhead for energy and everyone is connected to the same grid. The future of energy usage is, in my opinion, like moving from landlines to cell phones; every single house will have a way of generating its own power. Tesla’s energy business is working towards allowing people to reinstall their entire roofs with solar panels. This will be incredibly efficient and cost-efficient. Plus, it opens the doors to give remote communities access to energy where previously this was not possible. The focus of the company right now is still cars, but we are making movements on the energy side as well. I don’t know of other players in this space, but I hope other companies join us in this endeavor.


KC: What does your job as a data scientist look like on a day-to-day basis?


HZ: Data science is basically just statistics with an understanding of the engineering components and being able to communicate your findings well. What my team tries to do is use the massive amount of information that we collect from the cars to better understand how people interact with their cars. Our cars are fully electronic, which means we’re able to put sensors around the entire vehicle. At any given time, we’re tracking somewhere between 3000 and 5000 events that are happening in a car. This includes simple things like unlocking doors, rolling down the windows, opening the sunroof, adjusting seats – all of those actions have triggers, and we save that information inside the vehicles and later design them for better use.


For example, in a traditional car, it’s assumed that a windshield wiper gets used maybe 10,000 times during the life of the car. But we have statistics that can actually show how people are using them in x, y, z geographic regions, in certain weather conditions, and based on the individual. In providing that additional guidance, we can speculate more on what is expected usage. This work all falls under “proactive design”, which is figuring out how people actually use the parts.


The other side of my role is future prediction. Instead of having a car in a parking lot for 8-9 hours while someone is at work, in the future that car might also drive throughout the city during the day. We take all of the information that we know about how cars are being driven at certain times during the day and extrapolate that for future use.


KC: Why did you choose a dual degree at Michigan, and how did you pivot from a strictly math/business background into data science?


HZ: For my degree, business was just a new way for me to look at the world. I knew that if I dug too deep into the math side, not all of that information would be directly applicable to the real world. I wanted to study business just to keep myself grounded.


After I graduated from Michigan, I moved out west to do consulting for a small sales and marketing consulting company that mostly focused around healthcare. Healthcare is actually really interesting because there are a lot of new things happening in that field – regulations (on the policy side), but also new innovations, especially in the San Francisco area.


One project that I worked on at that consulting firm involved trying to predict the number of patients that would be diagnosed and treated for blood cancer, specifically leukemia and lymphoma. No one in my company knew how to code, and I was one of the few people who had taken a few programming classes when I was going through my undergraduate degree. I got roped into the project and it completely changed the way that I saw how people should interact with data.


After I saw the power of forecasting and programming with data analysis, I quit my job, took a few months to learn programming on my own, and went through a programming boot camp in San Francisco. At the end of the boot camp, Tesla was one of the companies that came to look at our presentations. I got lucky and ended up talking to the person who is now my current boss at Tesla. One thing has led to another throughout my career thus far, but it all started with the LSA education that allowed me to take interdisciplinary courses and seek out things that I was interested in.


KC: Did you partake in any extracurricular activities at U-M that ended up influencing your career path as well?


HZ: Yes! I was heavily involved in MPowered Entrepreneurship on campus. I saw this as a way for students who are excited about making a difference to get involved and engaged with the communities around them. My interest was mostly around the idea of adding value to other people’s lives (that’s kind of the root of entrepreneurship… finding a problem that other people haven’t tackled) and bringing innovative solutions to address those problems. It was at Michigan when I learned this idea of entrepreneurship and the power that it could have.


KC: What are your favorite and least favorite things about your job?


HZ: My favorite thing is that a lot of our work right now is really pushing boundaries. After growing up in Georgia, I moved to Michigan (my parents are actually still working for the University in Ann Arbor!). In the few years that I lived in Michigan, I saw the auto industry as being somewhat stagnant. Seeing a revolution evolve since then is super exciting. It’s kind of like the early 1900s again; we’re pushing new boundaries for the next generation of travel!


My least favorite part is that sometimes there are a lot of distractions and it can be hard to get a task done. There are so many things on our agenda that we are trying to tackle, so we’re not always doing one thing perfectly and then moving on to the next. A lot of my day requires balancing between all the different organizations that I support: design, manufacturing, engineering, supply chain, and finance. I try to support everyone, but my team right now is only three members, so we have a lot of busy days.


KC: To help students find opportunities in the automotive industry – are there any other automotive companies out there that are also doing REALLY innovative work?


HZ: I think there are a lot actually. I don’t know if Tesla is the company that put the pressure to the automotive industry or not, but other companies are now all looking into autonomy and self-driving vehicles, acquiring start-ups, and trying to figure out the future of car ownership. I think Ford, GM, and many other US auto companies are doing great work with their electric vehicle lines. They’re also huge players in the autonomous driving space, given their recent acquisitions.


In addition to other automotive companies, tech companies are also starting to get into this space as well. Google, for example, has a self-driving car division. Google has kind of been the front runner for autonomous cars – their hardware is fantastic. They’re testing their technology and it’s working almost flawlessly, from what I hear. Apple is also working on autonomous drive, and there are a bunch of other electric car companies working on building luxury cars.


KC: If you could share any advice with current students, what would you say?


HZ: 1. Take risks while you’re still on campus. There is no safer place to do something crazy with your interests than at Michigan, because there is a huge network of support; faculty members, friends, and even your parents are all there to back you up. It becomes a lot harder to do something like that once you enter the workforce. Our generation really focuses their time immediately after college on getting set on solid ground so they can succeed in the future. They see those first couple of years as super important for their development, which is completely true, but that also means that they can’t do things that are on the boundaries of their passions and interests. Take risks while you’re still at school; there’s no better time and no better place.


2. Try to reach out more to the alumni base. The alumni base LOVES to help. Actually in general, people love to help students. Take advantage of that title; you’re only a student for so long in your life. Make the most of that experience.


3. Take classes outside of what you know or want your future hobbies to be. If I hadn’t taken that Computer Science class on a whim, I would be where I am today. We are lucky enough to be at a school where that type of opportunity and flexibility is possible. Even an intro-level class gives you a good snapshot of what life in a particular field is like. Take the Intro to Econ or CS or Biology class just to see what it’s like; even if you’re an English or engineering major, taking classes outside your discipline will help you understand the opportunities around you. It will open your eyes to other things going on in the world, and it will teach you how to appreciate the difficulties that other people face in their fields.