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

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.

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.

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.

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).