February 11 is the “International Day of Women and Girls in Science.” To mark this special day, we asked CBIIT’s Associate Director for Informatics and Data Science (IDS), Dr. Jill Barnholtz-Sloan, to share her experience as a woman in science. In addition to serving as Associate Director of IDS, Dr. Barnholtz-Sloan is a senior investigator with an active research portfolio in the Trans-Divisional Research Program (TDRP), Division of Cancer Epidemiology and Genetics (DCEG). Her ability to view cancer research and data science from both a policy and a research perspective offers unique insight into what it’s like to be a woman in today’s data science field.

A lot has been written about the scarcity of young women in science, technology, engineering, and math—areas that serve as important pillars in data science. Do you think we’re doing a good job at showing young girls what’s possible?

Here at NCI, I’m fortunate to have a very diverse representation on my team. Females make up about 50 percent of my staff, from leadership positions all the way down the line. However, I know that’s not the case everywhere. According to a recent survey cited in Forbes, females made up only 15 percent of the data science field. Moreover, a study using data from the American Medical Informatics Association found that men led nearly 75 percent of U.S. academic informatics programs. Hopefully, over time, this gap in the data science field will narrow, as we focus on developing a more diverse, equitable and inclusive workforce.

Job opportunity certainly will help to close this gap. Females tend to be attracted to careers that give them more flexible work hours and where they can have a positive impact on the lives of others. In fact, studies show females consider working at a meaningful job more important than a higher salary (for example, see study by Hoffman and Friedman). In my experience, the field of data science can offer significant job flexibility with work location and hours and also compensate you appropriately based on your skills and experience. Most importantly, especially here at NCI, you have the opportunity to address one of the most pressing public health concerns of our day.

I would love to see more opportunities for young girls to learn about career trajectories in data science and biomedical research. It’s an exciting time for biomedical research and data science. Novel analytical techniques, such as artificial intelligence and natural language processing, coupled with the massive amount of cancer data generated each day, all are going to be vital in finding new ways for diagnosing, treating, and preventing cancer. Including females and fostering a diverse workforce will only strengthen the ability for novel discoveries, allowing for all voices and opinions to be heard and have impact.

Growing up and choosing your career in science, who were your biggest cheerleaders (or biggest critics)? Were any of them women?

I have been blessed in my training and career to have incredible mentors, both male and female. All of them were supportive and kind, but they also pushed me to think big and plan for the future. Having people in your life who challenge you to be “your best self” is critical to help you understand who you are and what you want to accomplish.

I’m especially thankful for two female mentors in my life. They not only showed me what “success” looks like—both in life and in research—but they were always honest with me (whether the feedback was good or bad) and helped me understand the scientific process. I continue to have close relationships with them both today!

My academic advisor in graduate school, who was male, also had a significant impact. He continuously asked me, “What do you want to do when you are done with your Ph.D.?” I kept telling him I needed more time in graduate school to decide. So he pushed me to serve as a teaching assistant for a class and also work on a research project so I could gain “real world” experience in both of these areas. I absolutely loved the research! I am so thankful for his constant pushing. It helped set me on the path I am on today.

It must have been difficult to leave a successful career in academia for NCI’s CBIIT. What led you to accept the position at CBIIT?

I had been in academia for a long time before moving to my positions at NCI. Through hard work and great collaborations, I was able to achieve a lot in academia. As with any position, I started to envision what the next stage in my career might be. Moving to NCI seemed like the ultimate step if I wanted to have a greater impact on cancer and use all my best skills. Working at NCI is like being at the “mothership” of cancer! The work we’re doing in informatics and data science at CBIIT is having an impact at both national and international levels. We’re making cancer data and tools more accessible, useable, and interoperable. Likewise, through my research in DCEG, we’re working hard to advance science that truly helps individuals with brain tumors and their families.      

We often hear that people’s path to data science is circuitous. Do you have advice for a woman who is considering switching her career path to data science?

Everyone’s path has twists and turns. The key is to end up at a place that works for you. My path to data science was from a mathematics and statistics standpoint, as there were no organized programs in data science when I was in undergraduate and graduate school.

Data science is a unique field because it depends on so many different perspectives. There are many ways that one can come to data science and have impact: mathematics and statistics (like me!), computer science, basic science (biology, genetics, etc.) and public health (as we are seeing with the COVID-19 pandemic). There are also a growing number of physicians who are interested and skilled in informatics stemming from their own use of electronic health record data for patient care and research.

Are you involved in mentoring today? If so, can you describe that relationship? What attributes/skills do you most wish to instill (or hone) as a mentor?

I actively mentor multiple individuals who are at varying stages in their careers, from high school students and graduate/medical students to professional staff and junior faculty. I try to have an open and transparent relationship, but approach all conversations, even the difficult ones, with kindness. Being a mother has taught me a lot about how far patience and kindness can take you. Even in the most difficult of situation, I’ve found that approaching it with kindness goes a long way toward helping to find workable solutions.

At the same time, I try to instill good scientific practice and rigor to analyses and presentation of results. That said, everyone is an individual and communicates in a unique way, hence I try to learn about each person I interact with and tailor my communication style to what works best for them.

Do you find you mentor women any differently than you do men?

My general approach to mentoring is the same for both females and males. I think any differences are highly nuanced. Successful mentoring requires getting to know the person, their likes/dislikes, communication style, and career goals, and then tailoring your approach appropriately. For example, my female mentors showed me how to be successful, as they were scientists, but also wives and mothers. My hope is that I can convey a similar success story for the young women I’m mentoring today.

Do you have any specific advice for women looking to make their mark in data science?

My best advice would be to not overlook how much opportunity there is in the data science field. Just as I made the move to NCI to have a more profound impact on the cancer research field, I think there are many areas where females can make a difference. Whatever your interests—molecular biology, genetics, public health, epidemiology, clinical practice, medications development, computer technology, informatics, statistics, programming, etc.,—this field has a place for you. Having more diversity not only will open more doors to a larger pool of skilled individuals, but also will likely strengthen our ability to make novel discoveries, as all viewpoints will be part of the scientific discussion.

The data science field is a great place to make a mark, and I hope more females, and frankly a larger pool of individuals in general, begin to see how they can help move this field, the data, and the tools we use forward to further advance cancer research and clinical care.