Adjunct Professor of Applied Analytics (Open Rank)

USC seeks adjunct professors to teach courses in our online Master of Science in Applied Analytics program. The successful candidate should possess a Ph.D., or equivalent professional degree, as well as relevant professional experience in the fields of analytics and artificial intelligence (or a Master’s degree with extensive professional experience in the field). Candidates must be currently employed in a primary position or career in the discipline (or retired from full time employment in the discipline). Candidates with a commitment to working collaboratively with colleagues and supporting students from a variety of backgrounds are especially desired. Preference will be given to candidates with significant prior online teaching experience combined with academic credentials, relevant professional experience in the field, and a history of receiving excellent teaching evaluations. In addition, the successful candidate will also demonstrate – through ideas, words, and actions – a strong commitment to USC’s Unifying Values. 

The specific courses for which we seek adjunct professors are:

• AAN 500: Applied Business Analytics and Artificial Intelligence

• AAN 505: Statistics for Applied Data Analytics

• AAN 510: Visualization and Storytelling With Data

• AAN 515: Regression Modeling for Applied Predictive Analytics

• AAN 520: Applied Data Management and Database Systems

• AAN 525: Applied Machine Learning for Business Applications

• AAN 530: Applied Optimization and Simulation

• AAN 535: Analytics Business Strategy and Communication

• AAN 540: Applications of Deep Learning and AI in Business

• AAN 545: Project Management for Analytics Professionals

• AAN 550: Applications in Artificial Intelligence

• AAN 555: Applied Analytics and Artificial Intelligence Capstone

Successful applicants will have expertise in technical applications used in the program’s curriculum, including but not limited to the following examples:

• Command line applications and prompting 

• Docker Desktop 

• Jupyter Notebook

• Pre-trained AI models and platforms (e.g., Transformers and HuggingFace)

• Python

• Machine learning platforms and libraries (e.g., H2O Model ML, PyTorch, TensorFlow, Keras) 

• Structured query language (SQL)

• Time series, spatial, relational, graph, and vector databases (e.g., PostGIS, Timescale, MobilityDB, EdgeQL, Apache AGE)

In applying for the position, please submit a resume or CV.

Responsibilities:

• Apply professional experience in academic teaching, assessment, institutional service, and collaborative work with colleagues.

• Demonstrate instructional preparation, planning, pacing, and organizational skills to effectively facilitate assigned courses.

• Deliver instructional content that aligns with course design and learning objectives and incorporates active learning opportunities for application of course content.

• Foster a collaborative learning environment that demonstrates responsiveness to student backgrounds, experiences, and cultures.

• Apply clear and effective presentation of course content in spoken, written, and visual communications, including elements of synchronous teaching style and asynchronous communications with students.

• Interact with students on a regular basis via announcements, discussion board posts, feedback on assignments, weekly office hours, and related synchronous and asynchronous modes of student engagement.

• Provide timely, substantive, constructive feedback and grades to improve student comprehension, performance, and application of course concepts and learning outcomes.

• Use student and peer evaluation data to reflect on instructional practices.

• Demonstrate a growth mindset by adapting teaching practices to continually improve instructional effectiveness.

Contract Term: Per semester

The hourly rates for this open rank position are Adjunct Assistant Professor $49.00, Adjunct Associate Professor $54.00; Adjunct Professor $59.00. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate’s work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.