Dozent gesucht für Auftrag - Academic Writer Artificial Intelligence Demand Forecast and Inventory Control (f/d/m)

Academic Writer Artificial Intelligence Demand Forecast and Inventory Control (f/d/m)

Course Title: Demand Forecast and Inventory Control

Study Programme: Master Artificial Intelligence, Distance Learning

Language: English

The course gives a general overview of traditional and modern methods used for demand forecasting and inventory control. Starting from the classic newsvendor model and its extensions, the course covers the fundamental aspects of dealing with uncertain demand, including censored data. Methods used for demand forecasting are explained, including traditional approaches such as exponential smoothing and ARIMA time-series analysis, as well as state-space models and structural time series-based approaches. Next, data-driven and machine learning based approaches are discussed, including methods that exploit the temporal order of, for example, sales data in the forecast and supervised methods that can be used without. To highlight the challenge in exploiting auto-correlation, the effects of causal relationships in time-series forecasting, in particular, temporal confounding are addressed. Further, methods that avoid demand forecasting altogether such as the “Big Data Newsvendor” and similar approaches are discussed. The course then turns towards inventory models, including, for example, models with a review such as (s,S) based models. Finally, the course includes a range of topics that are particularly important for practical applications, such as customer heterogeneity, or the retirement of old and inclusion of new products in the assortment, as well as discussing how to derive operational KPIs that can be used to monitor the replenishment process in practice.

Course Content
- Newsvendor model
- Traditional methods of demand forecasting
- Data-driven methods for demand forecasting
- Inventory models
- Further effects

What We Offer
- Remote and freelance contract
- Ability to develop your academic writing
- Guidelines and support from internal departments
- Opportunities to work on similar future projects

Your Responsibilities
- Creating a course book and reading list (130-180 pages) from an existing module description
- Creating various assessment types

Your Profile
- A completed academic degree and profile (Master or PhD) related to the subject area
- Industry experience and/or previous experience developing course materials is advantageous

For your application to be considered please submit the following documents (in English and in .pdf):
- CV
- Tailored cover letter (including your earliest start date)
- Writing sample: any academic text written by the candidate
- Academic transcripts

We look forward to receiving your application. Applications are reviewed on a rolling basis, so we encourage you to submit your application as soon as possible.

Please note that we cannot accept applications via email.