Hiring Clinical Faculty for 2025: Interview with CDS Clinical Assistant Professor Sidharth Sah
In a fast-evolving field like data science, teaching excellence plays a vital role in preparing the next generation of practitioners. CDS is currently hiring clinical faculty. The role involves teaching and coordinating three entry and advanced-level courses each semester in areas such as machine learning, programming, computer vision, artificial intelligence, natural language processing, and data visualization.
For those interested in joining the center, we spoke with Clinical Assistant Professor Sidharth Sah about his experience since joining CDS seven months ago. (We’ve also previously interviewed Louis Mittel and Pascal Wallisch in their roles as CDS clinical faculty.) This interview has been lightly edited for clarity.
What most appealed to you about the position at CDS and what makes it special?
The courses really align with my interests in theoretical approaches and working with data. When you’re teaching, having engaged students is crucial, and that’s definitely been true here. Personally, being in New York was also a major draw — the city offers incredible opportunities.
How would you define a clinical faculty member at CDS, and how does the workload differ from non-clinical faculty?
A clinical faculty member’s primary focus is teaching. It’s a full-time commitment to education rather than research, which differs from tenure-track positions.
Can you share the most rewarding aspects of your role?
I particularly enjoy one-on-one interactions with students. Whether it’s after class, during office hours, or in meetings, it’s deeply satisfying when a student shows genuine interest in the material. Drawing concepts on the whiteboard and seeing them grasp something in a deeper way — that’s always what I enjoy most.
Can you share the most challenging aspects of your role?
The main challenge lies in teaching students with varying levels of background knowledge and different interests. I teach three courses: causal inference, linear regression models, and survey in data science. For example, in the survey course, which is designed for non-majors, I might have students who’ve never written code sitting alongside computer science majors. Finding the right balance of formal mathematics, real-world examples, and conceptual explanations to engage everyone can be challenging.
What’s something you’ve learned during your time as clinical faculty that pleasantly surprised you?
The interdisciplinary nature of data science has been enlightening. Coming from an economics background, I’ve found significant common ground between different fields’ approaches to similar problems. Often, it’s just a matter of framing the same ideas from different perspectives.
What’s the greatest benefit of being a clinical faculty member?
As someone who loves teaching, I appreciate that it’s the core focus of my role. I can dedicate all my energy to improving course materials, crafting effective assignments, and meeting with students. Having the time to make myself available outside regular office hours allows me to fully commit to making my courses as strong as possible.
What advice do you have for someone stepping into this position?
Make the courses your own. While there might be existing materials and typical syllabi, focusing on what you find interesting and important ultimately creates a better experience. It requires more work to develop your own material, but it pays off in making the class more engaging.
Lastly, are there any other elements about the role that you would like to emphasize?
I currently teach both in-person and online courses, which offers valuable flexibility in reaching different student populations. The variety in teaching modalities adds another dimension to the role.
For more information on the open Clinical Faculty position, see its full description on Interfolio.
By Stephen Thomas
