Jerry Chi is a Data Scientist at Indeed Tokyo and has experience in analytics and data engineering at various tech companies. In this blog, he talks about his role as a data scientist and the characteristics he looks out for, for someone joining his team.
Jerry is originally from Silicon Valley and has lived in different places across the globe such as Korea, China and Finland to name a few.
He has a passion for learning and gives insights into his role at Indeed and what he looks for in someone joining his team.
Addicted to self-improvement and learning, Jerry graduated from Stanford in Management Science & Engineering. He received an MBA and a Masters of Arts in International Studies from University of Pennsylvania (Wharton) as well as attended five study abroad programs over the years. In addition to that, he highlights how he has learnt a great deal by taking initiative and learning through his experiences.
“My data science knowledge was largely picked up informally – through online courses, reading blogs, watching videos and being on the job,” Jerry shares.
His work experience has been varied with a background from tech companies as well as his own startup.
“My past jobs involved analytics, machine learning, and data engineering at Google, Supercell (a mobile game developer), and SmartNews (a news app developer), where I built the data science team from scratch. I also started my own company shortly after college; it didn’t go well, but I learned a lot,” he recalls.
In his role as a data scientist at Indeed based in Tokyo, he co-leads a team of engineers and data scientists to build and improve a large-scale recommendation system powered by machine learning.
One of the aspects he is excited about in his role is doing innovative experimentation with fundamentally different machine learning techniques.
“Indeed has a large percentage of core product development (mostly serving global markets) happening in APAC offices,” Jerry explains. “This is different from most companies where the vast majority of the important product development happens in the country where they’re headquartered. It’s great that I can have this much global impact working out of Tokyo, which is maybe not possible at many other tech companies.”
Jerry also shares one of the challenges in his role and how he manages to overcome it.
“Doing machine learning operations (MLops) well is a multifaceted and nontrivial challenge. We have extensive internal tooling to streamline MLops as well as various teams and individuals to advise on the topic based on their ML experience,” he explains.
As he leans on various teams and co-workers to overcome this challenge, Jerry stresses the importance of learning and shares other factors which are beneficial to becoming a successful data scientist.
“It’s helpful to have a passion for learning combined with careful prioritization skills. Data science methods, tools, and techniques keep evolving and improving, and you want to learn the helpful things, but you can never learn them all,” he says.
“I also learned a lot about the HR tech industry and how jobseekers and employers think and behave; internally, we have lots of great research and analysis to help with this learning,” Jerry shares.
When looking out for people to join his team, Jerry looks for both aptitude and attitude.
“I’m looking for fast learners who are passionate about data science and who empathize with Indeed’s mission”
Read more: Jerry’s guide to working with… Jerry
Jerry’s favorite thing about working at Indeed?
“The company mission of ‘we help people get jobs’ is simple, with meaningful social impact, and colleagues really mean it when they say that they are focused on this mission”
We are expanding the data science team, and if you are passionate about data science and obsessed with learning and personal growth, check out our available roles on indeed.jobs.
You can also read more about Jerry’s take on how to be a successful data scientist here, or see all available roles at Indeed Japan here.