Teaching Careers (for Statisticians): What You Should Know

Editor’s note: This was originally published on Mine’s blog, Data Pedagogy, in August. It has been republished with permission.

Mine Dogucu is an assistant professor of teaching in the department of statistics at the University of California, Irvine. She is co-author of the upcoming book Bayes Rules! An Introduction to Bayesian Modeling with R. She is also the co-chair of the national Undergraduate Statistics Project Competition and Electronic Undergraduate Statistics Research Conference. Her work focuses on modernizing the statistics curriculum, making data science accessible, and educating undergraduates about Bayesian techniques.

At the beginning of the month, I was on a panel titled “Teaching-Focused Careers in Colleges, Universities, and Industry.” The other panelists were Garrett Grolemund, Rebecca Nugent, and Katie St. Clair. The panel was chaired by Beth Chance. I will summarize a few points I made during my talk.

Misconceptions

I have always been interested in teaching careers. I have taught at liberal arts colleges and research universities. Despite my interest in teaching positions, I knew little about them during my graduate school years. I will share some misconceptions I had.

• Teaching-focused careers are only at small liberal arts colleges (SLACs). I had this misconception mainly because I went to a liberal arts college. I only applied to SLACs in my last year during my PhD. After finishing my PhD, I met other statistics educators in different kinds of institutions. I now know that teaching-focused careers are even possible in industry.
• Research universities only have teaching positions that are non-tenure track. I had this misconception because this was the case at my PhD alma mater. I know this is not true because the position I currently hold is a tenure-track one. Even though tenure-track teaching positions are not as common in research universities, there are other positions that are long-term (e.g., Duke University’s professor of the practice or Amherst College’s lecturer).
• Teaching load is higher in research universities for teaching faculty. This may or may not be a misconception from a statistics perspective. I do not have any data on this. However, in my case, my teaching load has stayed almost the same between SLACs and research universities.

What Does the Job Look Like?

I teach at the University of California (UC), Irvine, which is one of the 10 UC campuses. We have about 36,000 students; about 30,000 are undergraduate students. About 45 percent of the undergraduate students are first-generation. I teach in the department of statistics. We do not have a bachelor’s degree in statistics, but we do have a bachelor’s degree in data science. We are on a quarterly system, and my teaching load is 2-2-2 pre-tenure. This would be equivalent to a 2-2 teaching load in the semester system. In case you are not familiar with the term “teaching load,” it is essentially the number of courses one has to teach. A 2-2 teaching load would mean 2 courses in the fall and 2 in the spring.

My typical work week mainly consists of teaching and preparing for teaching. I spend a lot of my time preparing material—(now) videos—and assignments for my students and sharing them on my course websites. I hold office hours. I also hold teaching office hours, when (graduate) students and faculty come to ask me questions related to teaching. On a weekly basis, I attend meetings: with my TAs and graders; with my department; and with my collaborators. To meet with my collaborators, I have to work on tasks related to our projects.

Rewards and Challenges

As I had the chance to teach both at SLACs and research universities, I have been able to make some comparisons and have found both SLAC teaching and research university teaching to be fulfilling in their own ways.

Small class sizes. SLACs have smaller class sizes. I even taught a course for seven students once. Small class sizes have given me a great opportunity to get to know my students and witness their process closely, which has been rewarding.

With a small class, however, came a bigger demand for my time. I had much more face time with my students because there is an open-door policy for students and other faculty at SLACs. It felt great to be part of such a community, though it left me with limited time for my own projects.

Large class sizes. Teaching large classes can be challenging from a course management perspective. I should also note that not all classes I teach are large classes. For instance, I teach a Bayesian course that is always capped at 30.

Teaching large classes will always be a challenge but it is also possible to learn teaching methods and tools to teach more effectively in large classes. Teaching a large class also means teaching with a team of teaching assistants (TAs) and graders. Working with a teaching team provides me the opportunity to learn from graduate students, as well. And being in a department with graduate students (which is rare in SLACs) gives me the opportunity to work with them on pedagogical projects.

SLACs cherish teaching, and most faculty members are evaluated with similar expectations when it comes to teaching and research. The culture around teaching usually is a positive one. At research universities on the other hand, research faculty are bigger in number and thus the culture around teaching varies from department to department. Having to explain yourself, your projects, and your research—which may be different from what other faculty define as research—can be challenging.

Resources

I want to recommend a few resources I hope will help anyone considering a teaching-focused career.

Networks

Section on Statistics and Data Science Education Mentoring Program
This program matches a junior statistics educator with a senior statistics educator colleague. When I was a graduate student, I took part in the program twice and had Jeff Witmer and Jo Hardin as my mentors. I have learned a lot from them!

Preparing to Teach Workshop
This workshop teaches how to teach and prepare for the job market for teaching-focused careers. The workshop usually takes place during major conferences such as JSM and eCOTS.

Isolated Statisticians Interest Group
This is essentially an email list with members from mostly SLACs.

Preparing to Teach National Network
This network is not related to the aforementioned workshop. This is a program that runs in many universities and matches a graduate student with a mentor at a SLAC. Check if your university has this program. My university had it, and I was a Preparing to Teach fellow at Denison University. I learned a lot about academic careers by enrolling in this program.

Tips for the Job Market

In this section, I try to provide tips I seldom see. Some might seem random but that is because I wish someone had told me about them when I was on the job market.

Before Getting on the Job Market

• Teach! Even if it is an hour-long workshop.
• Get some pedagogical training. Check your school’s education courses or certificates in college teaching.
• Have a website.
• Be vocal (beyond statistics networks, as well). There are jobs outside of statistics departments (e.g., in business schools, medical schools, etc.) that may be well suited for statistics educators.
• Make connections at JSM and other conferences with statistics educators, not only for the job market but because you may want to share ideas and conduct projects in the long run.
• Prepare your job application materials (at least in first draft) the summer before. This gives you an organized frame of thinking about your experiences and what you would like to do in your future job. Having this in an organized manner on paper, and on your mind, will make talking to others at conferences and elsewhere much easier.

While on the Job Market

• Reach out to the person who emailed/posted the job ad or the person whose name is provided as the point of contact. Knowing more about a job has helped me either 1) decide not to apply for a job because it was not what I wanted to do with my career or 2) make my application stronger because I knew what I was looking for.
• Ask what is considered “research.” Faculty are evaluated by their teaching, research, and service. However, each department/school interprets research differently for statisticians and statistics educators. Where does pedagogical writing (e.g., textbook) fall under faculty evaluation? What about collaborative research?
• Ask about tech infrastructure and support. Your innovative teaching will be highly dependent on it.
• Be emotionally ready to meet faculty who look down on teaching. You will also meet such faculty in your career, as well. It can be a challenging situation to handle during job interviews.
• If you feel comfortable, ask about dual-career support. Asking early will give you the time to plan for your partner, as well. This way, finding a job for your partner does not have to happen within a week after receiving the offer. This is completely my personal view on the topic.

After Getting an Offer

• The teaching load for the first few years may be negotiable.
• Ask about funds after tenure, even if it is minimal support. The offer letter you receive will most likely have a start-up fund you can use pre-tenure. In SLACs where faculty are not expected to bring in grant money, there are funds available to faculty for tech products, student hiring, etc. Ask!
• If you are an immigrant, it is your right to ask what immigration support the employer provides.
• Moving is more costly than you might think. If your offer letter does not include moving costs, you can ask. If it does, check with moving companies/options to see if the funds will be enough.