What initially made you interested in data science?

My interest in data science was sparked during my undergraduate studies, where I double majored in Mathematics and Business Analytics. I saw data science as a natural extension of these two fields, combining the analytical and quantitative skills of mathematics with the practical applications of business analytics. I was drawn to the broad range of topics that data science encompasses, from data engineering, model building, to data analysis.

What was your practicum project and what did you learn from it?

I did my practicum project by interning at Meta as a data scientist intern, which allowed me to immerse myself in the role of a data scientist working collaboratively with cross-functional stakeholders to enhance product features. This experience offered me valuable insights into effectively communicating technical results to stakeholders with diverse backgrounds and contexts.

What are your plans following the program?

I'll be working at the Data & AI team at BlackRock, providing data services and solutions to support the company platforms and to onboard new portfolios.

How do you feel the program has helped you prepare for your future in data science?

The program's emphasis on mathematical and statistical fundamentals has served as a springboard for my deeper comprehension of the underlying mechanism of models. A lot of the times, coding is not the most difficult part for me but finding the right direction is more important. Additionally, with a better understanding of the statistical assumptions and mathematical derivation of algorithms, I can communicate my ideas about decision-making more effectively to others.