Adjunct Associate Faculty, Analytics for Cybersecurity Management (On-Campus, Fall '26)

Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds to pursue greater human understanding, pioneering discoveries, and service to society.

The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good.

Seeking analytics professionals to serve as a part-time Associate for a graduate-level course on Analytics for Cybersecurity Management. An Associate is a faculty line junior to a Lecturer, that provides subject matter expertise and supports the instructional process for a course section. Serving as an Associate is an outstanding way to gain exposure to graduate-level teaching at Columbia University.

This course offers a comprehensive introduction to core cybersecurity principles, encompassing network security, threat detection, and vulnerability management, while highlighting how emerging techniques in AI and machine learning can transform modern defense strategies. Students will explore key frameworks, advanced tools, and real-world case studies, gaining insight into how analytics underpins effective threat intelligence, incident response, and regulatory compliance.

Through hands-on exercises, interactive assignments, and a culminating project focused on automating vulnerability analysis, learners will develop practical skills in data-driven security. They will practice essential tasks—such as parsing logs, classifying vulnerabilities, creating visual dashboards, and applying AI-driven anomaly detection—while also examining ethical, legal, and regulatory considerations in cybersecurity. By the end of the course, students will be equipped to design proactive defense measures, critically assess diverse threat landscapes, and responsibly leverage AI and analytics to fortify digital ecosystems against evolving cyber risks.

Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting.

Responsibilities

Attend all class sessions, assist with instruction, lead breakout sessions, facilitate discussions.; Evaluate, grade student work and assessments as requested by the course Lecturer.; Monitor and address student concerns and inquiries.

Requirements

Graduate degree in a relevant field such as Cybersecurity, Computer Science, Data Science/Analytics, Information Systems, Information Security, Electrical/Computer Engineering, Statistics, or a closely related discipline.; 3+ years of professional experience in roles such as Security Operations (SOC), Threat Intelligence, Incident Response, Security Engineering, Vulnerability Management, Cloud Security, or Applied Data Science/ML for security within industries like technology, finance, healthcare, consulting, or government.; Python proficiency for data parsing/ETL, log analysis, and basic analytics (e.g., pandas, simple scikit-learn workflows).; Comfort with shell scripting (PowerShell and/or Bash) and core OS tools for processes, networking, and files.; Strong communication and feedback skills for guiding graduate students, dependable, organized, and detail-oriented

Nice to have

University teaching or TA experience, especially in graduate or professional programs.; Experience with cloud security (IAM, least privilege, security groups, logging) and common tools (e.g., CloudTrail/Defender for Cloud).; Familiarity with SOAR concepts/workflows and alert triage/runbooks.; Practical knowledge of security/privacy frameworks and regs (e.g., NIST CSF, HIPAA, GDPR) and ethical handling of sensitive data.; Experience supporting course operations (Canvas/LMS, rubric-based grading, timely feedback, academic integrity processes, managing small-group activities).; Track record of mentoring early-career professionals or graduate students and collaborating in diverse, remote teams.