“Indistinguishable from magic?” If you ask Chun Schiros, Data Science group manager, that statement explains part of her fascination with data science, and part of the reason she chose this field as a career. But the journey to get to where she is now has taken her to some unexpected places … placing her in a growing, evolving field, and as a pioneering woman in that space.
We recently sat down with Chun to get some background on her passion for data science and why there might be more “magic” in the field than you might have considered.
What are some things about data science that you’re passionate about?
The most exciting parts of data science, to me, are learning, discovery and innovation. For every use case, we get to dive into the raw data, understand the business process and workflow. Then, we use a blend of tools, mathematical algorithms, AI and machine learning principles to discover hidden patterns from the raw data, draw conclusions, make recommendations and find innovative solutions that are purposeful, trustworthy and efficient for our bankers and customers.
No two projects are the same, and we are constantly learning along the journey as we work with the data to solve problems every day.
What about your work do you think people most misunderstand?
There is a statement from a writer I love that I like to paraphrase: “Any sufficiently advanced technology is indistinguishable from magic.” For me, it sometimes feels like data scientists are viewed to have mystical, magical powers that can solve any problem. All you have to do is run data through the perfect data science machine to produce the desired results to everyone’s problem, like magic.
It would be really nice if it worked that way! But no two data science solutions are the same. A useful data solution requires the right understanding of the business problem. And the best way to create value from data science is to have multi-disciplinary teams – with representation from the business, products, engineering and data science – working together to develop cross-functional understanding of the needs and opportunities, which leads to better solutions and business results.
What made you interested in working in data science? How did you end up in this field?
I have always been passionate about data and math and using them to discover truth. I chose Physics as my focus at high school and majored in engineering in college. During college, I was fascinated by automatic facial recognition and chose to do my thesis on it. I continued to pursue a PhD in electrical engineering in the US, focusing on digital imaging processing, particularly in the medical field.
Throughout, I collected or created so much data through images and image reconstruction that I became interested in learning how to draw hidden insights from it. I took another Master’s degree in statistics, and used data, statistical models and experimental design to test hypotheses that lead to more accurate clinical diagnosis and surgical decisioning.
I continued to work in data science, but in the financial sector. To me, data science provides something I don’t see everywhere – unparalleled commonality, ubiquity. No matter where you find data – and you can find it everywhere — you can learn something from it that betters people’s lives.
What opportunities do you see for people – especially women – who are interested in getting into this field? Why should someone consider it?
The opportunities in data science are enormous! The industry is rapidly evolving into one of the most exciting professions of the 21st century.
The reason is that data is unparalleled in ubiquity. Big Data and cloud computing are enabling data science and AI to change our world in amazing ways. Data Scientists are in great demand and at the forefront of coming AI revolution, from making new life-saving medicines to self-driving cars to personalized financial guidance and so on. Data science is a rapidly evolving area with the growing amount of data available to analyze and the new technology to learn and adopt. The industry is ideal for any one with curious minds who love solving everyday puzzles using data.
What to you is the most interesting/coolest/most rewarding aspect of working at a bank and being involved in data
The most rewarding aspect of working at a bank and in data is seeing how our data products and services help customers achieve their financial goals.
At the end of the day, it is not about what we do, but about the value we provide to people that matters. Leveraging data and financial knowledge, I get to be part of a journey that helps our customers grow, reduces financial stress, and provides purposeful financial guidance and services where they need them and when they need them. It is the best and most rewarding part of my job.
Chun has recently been a guest on two data and analytics podcasts:
AI Time Journal
Chun speaks about her background, how we use data at Regions, the significance of model drift in using data and more.
Business of Data
In this podcast, Chun discusses the importance of trustworthy AI and having an open, transparent methodology that delivers value for everyone.
“We started right from the beginning, taking the user along with us when designing the product,” she explains. “We start with an MVP [minimum viable product] with minimal features, so that we can iterate the product throughout its cycle and use the feedback we get to improve the product. This way, we can really understand the users’ needs and create ownership for the user.”