Statistics is perhaps one of the few professions that have seen steady job growth in the past 30 years or so, and the need for statisticians continues to grow today. Due to the applied nature of statistics, graduate students often find themselves landing on a job in a highly collaborative environment (e.g., medicine, public health) that requires not only good training in statistics, but also a fair understanding of subject matter, and perhaps more importantly, skills needed to be able to collaborate as a team member with non-statisticians. Most likely these important skills are not taught in classrooms and could potentially hinder the career growth of a statistician. 

My career path, though not academic, is hardly “alternative”. With constant soul-searching along the way, I have managed to stick with science and marched in the space of drug discovery and development in pharmaceutical industry.  It is definitely not a straightforward path, contrary to what people often perceive.  There were numerous moments of uncertainties. Nevertheless, it has been a rewarding journey so far.

If science happens at a bench, and no one ever hears about it, did it really happen? The students in Thinkers and Drinkers, don’t think so, and they embarked on a journey to tell the people of Rochester what kind of science is happening in their backyard.  With stylish, matching T-shirts, these scientists put themselves on the frontline to defend science and add the human angle that is often missing from articles published about science.

On Friday March 10, University of Rochester’s Broadening Experiences in Scientific Training (URBEST) brought together seven Science Communicators from University of Rochester, Rochester Institute of Technology, University of Washington, and National Public Radio (NPR). Maddie Sofia, assistant producer at NPR and recent alumna (’16), returned to UR to share her triumphs and tribulations with PhD graduate students and postdocs at the URBEST Career Story. The real fun, however, happened at a morning and afternoon session of Better Science Communication Through Impov.

Those of us that want to be college educators, yet are still in our PhD training, face the problem of experience. As is the case with any job graduate students and post-docs will be applying for, you need experience. The gold standard for experience in order to be a faculty member at a primarily undergraduate institution is teaching in the classroom. Previously I have shared a collaborative approach that I took to achieve experience in the classroom through an American Society of Cell Biology’s program. These types of opportunities, however, can be few in number and hard to find. When looking for teaching at the college level, this commonly leads to the adjunct position. This is working on a semester-by-semester basis to teach one or more courses at a college or university.

Several recent alumni from the department of Brain and Cognitive Science have gone into the field of data science, which is an increasingly popular alternative to academia for people in our field. It is said that 90% of the world's data has been generated in the past 2 years, and it is a reasonable assumption that the same proportion of the world’s data scientists have entered the field in the same amount of time.  Here’s a summary I put together of the initial steps others have taken in preparation for getting a job in data science following graduation. 

            Along with a history of advances in biomedical research, scientists at UR have established a legacy of outreach and service. Dr. William F. Neuman was a founder and Chair of the Department of Radiation Biology and Biophysics at UR, which stemmed from his work with the Manhattan Project. He was a world-renowned expert in the musculoskeletal field who made significant contributions into the understanding of bone matrix physiology and hormonal effects on bone structure. However, in addition to his work in orthopedics, Dr. Neuman believed that scientists should serve their communities and be “good people.”

The digital revolution, coupled with the availability of vast data systems, has helped human beings recognize the importance of using data to make informed decisions. This has stimulated the development of data science, an interdisciplinary field that seeks to create tools and systems to collect, process, and analyze modern data warehouses in order to solve real-world problems. That’s why we (Shiyang Ma, 3^rd Year PhD Student in Statistics, Huiwen Xu, 3^rd Year PhD Student in Health Services Research, Adan Z. Becerra, 5^th Year PhD Student in Epidemiology, and Zhengyuan Yang, 1^st Year PhD Student in Computer Science) decided to establish the Rochester Data Science Society (RDSS), the first ever student organization at the University of Rochester that serves all students interested in data science, statistics, computer science, engineering, health analytics, economics, or other related fields. Our varying interests and fields of study attest to the multidisciplinary nature of data science as well as its potential to impact the world.

Some people arrive on day one of graduate school ready to tackle their favorite project, cure a disease, or solve an important problem. I got to graduate school without one idea of what I wanted to do. All I knew was that I loved learning science and I could keep doing that while I figured out what I wanted to do with my life. Thankfully, my time as a graduate student at Â鶹ÊÓƵwas a transformational time of learning, not just science, but also about myself. Here are some of the lessons that I learned and helped get me where I am now: Director of Field Applications in the scientific instrumentation company, Unchained Labs.