Advanced Social Network Analysis (SNA) Instructor - Part-Time - TS/SCI with Polygraph Required

• Serve as an instructor for the previously developed course curriculum
• Set up and guide students through coding environments, following provided instructions and resources.
• Teach Python fundamentals and advanced concepts, with a focus on the pandas library and class-specific Python packages.
• Introduce and review SNA (Social Network Analysis) concepts, ensuring students grasp methodological foundations.
• Educate students on community detection, pattern analysis, and temporal analysis techniques.
• Train students to use specialized graph visualization software provided by the course curriculum.
• Highlight the broad applicability and interdisciplinary relevance of Social Network Analysis across various data types and industries.
• Facilitate understanding of analytical methodologies and their practical implementation through hands-on examples and exercises.
• Provide guidance and support to students for mastering both technical tools and theoretical concepts.
• Provide student support and troubleshooting
• Prepare and submit written post-course feedback to help refine course curriculum
• Work with an instructional designer to refresh/update the SNA course as needed.

Required

• Strong knowledge of Social Network Analysis (SNA) principles, including graph theory, community detection, and network visualization.
• Proficiency in Python programming, including data manipulation with pandas, and experience with graph-related Python libraries.
• Experience with graph visualization tools and familiarity with temporal and pattern analysis.
• Proven teaching or instructional experience, with excellent communication and facilitation skills.
• Ability to make abstract and technical concepts accessible to a wide variety of learners.
• Strong organizational skills, with experience in preparing and delivering instructional content.
• Bachelor’s Degree in applicable discipline.
• TS/SCI with polygraph.

Desired

• Experience working in customer analytic environment.
• Proficiency with client-specific tools.