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 seventeen 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.
Job Description
The School of Professional Studies seeks experienced industry professionals to serve as part-time Lecturer for a graduate-level course in Analytics for Cybersecurity Management. 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.
Responsibilities
Lead class lectures, instructional activities, and classroom discussions. Attend all class sessions.
Monitor and address student concerns and inquiries.
Evaluate and grade student work and assessments.
Conduct office hours.
Qualifications
Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training and a record of accomplishment as practitioners in an applied industry setting.
Requirements
Doctoral degree in a quantitative disciplinary area
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
Preferred Skills & Experience
10+ years of related professional experience.
2+ years of University teaching experience, ideally at the graduate level.
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.