Adjunct Instructor in Time Series Forecasting and Operational Analytics

Brandeis University’s Online Applied Data Science and Decision Analytics Program is seeking an Adjunct Faculty member for RADS 135 Time Series Forecasting and Operational Analytics for the Fall-2 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Applied Data Science and Decision Analytics. This course will cover predictive modeling and forecasting under uncertainty, including ARIMA, Prophet, and deep learning approaches for sustainable operations.

Responsibilities

Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms; Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation; Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe; Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.

Requirements

Advanced degree (Masters or Ph.D) in Statistics, Operational Research, Data Science or a related field; Professional experience applying forecasting methods to operational demands, planning, or in sustainability contexts; Expertise in time series analysis and forecasting under uncertainty, including ARMIA and modern machine learning approach; At least 1 year of teaching or training experience (preferably online/asynchronous); Experience with online instruction; Excellent communication and teaching skills in an online learning environment.

Nice to have

Prior online teaching experience at the graduate level; Knowledge of global learner personas and culturally responsive pedagogy; Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)