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How did you become a data scientist at ����Ӱҵ?

I completed my undergraduate degree in Mathematics at the University of California, Los Angeles, and for graduate school I headed to Hawaii to continue my studies in math. Initially, I thought I wanted to become a math professor, but I changed my mind and landed a data science internship at ����Ӱҵ.

As an intern, one of my tasks was to determine the optimal timing, frequency, and communication methods for contacting our Financial Planners to maximize sales. It was an open-ended problem, and I found it very cool. I really appreciate ����Ӱҵ’s culture of innovation because I am, at my core, a problem solver.

At the end of my internship experience, I was in the final year of my PhD, which meant no coursework or compelling reasons to return to Hawaii. Fortunately, our team was actively seeking data scientists and I was hired. 

What is a typical day like for you as a data scientist?

As a data scientist, I view my role as quantifying and providing solutions for various business problems using the available data. A typical day can involve anything from creating predictive models to wrangling data and creating data pipelines. I spend time analyzing data and presenting findings to stakeholders – whether it’s initial insights or model results.

How do you feel supported in your career development?

Being given the space to grow according to our team’s needs has been crucial for me. Last year, our team was working on putting a model into production – a common pain point for data scientists. There isn’t a single established way to seamlessly transition data from the model to a business-consumable format. In this context, I took on part of a project: creating a data pipeline that automatically ran the model on new inputs and wrote the output to our database. Whether it’s tables or other structures, the goal was to make the data accessible. As a result, I’ve decided to pursue certifications this year to deepen my understanding of this process. The pivotal moment? A conversation with my manager. I noticed we were falling behind on a project and asked, ‘Can I take care of it?’ Her response? ‘Yes!’

What makes ����Ӱҵ a great place to work?

Considering the size of our company and the industry we operate in, it’s remarkable how well we’ve embraced new technologies and how committed we are to doing things in the best possible way.

What’s the most valuable lesson you’ve learned in your role?

Early in my internship, my mentor emphasized a crucial aspect of storytelling. It was during the second week, and she had asked me a few leading questions to get me started with the exploratory data analysis stage of my internship project. When I returned with a dozen graphs, she posed a simple yet profound question: “Why?”

She’s not only a skilled data scientist but also an exceptional mentor. Her emphasis on the “why” has shaped my approach, making me more thoughtful and purpose-driven in my work.