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

LMI•McLean, VA

21d

About The Position

LMI is looking for an experienced Advanced Social Network Analysis (SNA) Instructor to join our team on a part-time/hourly basis. The instructor will deliver advanced SNA courses in support of a U.S. Federal Government Agency working with classified media. The course, titled Advanced Social Network Analysis , is a three -day program held once per quarter . This is an advanced-level instructional role requiring both technical expertise and the ability to engage and inspire students. A successful candidate will enjoy translating complex methodologies into practical, real-world use cases and empowering learners with cutting-edge analysis tools .

Requirements

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.

Nice To Haves

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

Responsibilities

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 p andas 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.