Alumni Spotlight: Ruthe Huang, ScM ’19

Ruthe Huang, ScM '19, works for Practical Intelligence as a Senior Data Scientist, where she specializes in statistical modeling and data visualization. Her thesis, under the direction of Mei-Cheng Wang, was entitled "ADHD Risk Prediction in the Boston Birth Cohort: an Application of the Proportional Odds Model and ROC Curve Analysis.”

In her spare time, Huang volunteers for the Prison-to-Professionals program, tutoring math, statistics, and standardized test prep to criminal-justice involved groups. 2024 marks her seventh year working with the organization as their SAT/GRE Facilitator.

Describe your current position and responsibilities in a way that will inform current and prospective students about career opportunities in biostatistics.

I am a data scientist within the government contracting world, meaning that each client and problem set is never the same. For the last four years, I have been working for a Department of Defense client with uniquely frustrating data problems, including naïve and nontraditional sources of data, mission limitations to software and data access, and stakeholder distrust in statistical results. Much of my daily work involves not just data cleaning and statistical analysis but also working with software teams to deploy data products as well as presenting analytical results for a variety of audiences.

What sparked your interest in the field of biostatistics?

Early on in my undergraduate studies, I looked for a career field that would combine my two interests of public health and statistics; biostatistics was the perfect match. I loved that biostatistics was interdisciplinary, allowing me to master quantitative methods while still working in the realm of public health.

What led you to join the Johns Hopkins Department of Biostatistics?

I was biased in my decision, since I was a Hopkins undergrad and had the chance to experience how wonderful the faculty were before starting at Bloomberg. However, the ultimate decision came down to the small cohorts and robust statistical training that the Department offered.

I still find it challenging to convince stakeholders who are not familiar with data or quantitative methods to believe in the results of statistical modeling, but Dr. Zeger’s courses gave me the tools to continue improving my skills.

How did your degree prepare you for your career? What aspects of the Hopkins Biostatistics program did you find most useful?

The coursework of the ScM program took us through such rigorous detail that I left with the skillsets – and, more importantly, the confidence – to not fear strange or new data problems. In my career, I often face unorthodox problems with messy data; although I may not have learned how to deal with these problem sets through coursework, I have been able to apply foundational knowledge from our program to help clients conduct as robust of an analysis as possible or even help clients develop novel approaches.

In his Methods series, Dr. Zeger would often emphasize the importance of interpreting model results clearly and accurately. I think of this often in my career, as I find most of my presentations directed to (statistically) non-technical audiences. I still find it challenging to convince stakeholders who are not familiar with data or quantitative methods to believe in the results of statistical modeling, but Dr. Zeger’s courses gave me the tools to continue improving my skills.

What has been your most satisfying job experience using your biostatistics background?

It is often said that building data models is an art, not a science. I experienced this first-hand when I was able to identify a key result in data using only contextual knowledge and basic model-building techniques. A different organization analyzed the same dataset and used only machine learning algorithms. The other organization was not able to identify the key result from my simple classification model because they had not taken the time to understand the context from which the data came nor check the data assumption of using certain models.

How did you build your sense of community during your time as a Biostatistics student?

My cohort was the best part of my time as a Biostatistics student. Because we were a small group of six, we were able to spend a lot of time together both at Bloomberg as well as in our personal time. From working on assignments in our office to picking apples in Baltimore County, we were able to be a community of support for each other.

What was your favorite thing about living in Baltimore when you were a student?

My favorite thing about living in Baltimore as a student was exploring all the little pleasures the city has to offer. I always loved that Baltimore was a relatively small city, because it meant that there were less crowds to navigate through while enjoy the beautiful magnolia blossoms by the Washington Monument, eating the whole menu at Ekiben, or sweating your body weight at Artscape. Baltimore is beautiful in its juxtaposition: of loud and quiet, of dark and light, of chaotic and beautiful.

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