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Master thesis S&OP - Probabilistic Market Scenario Modelling
Volvo Group
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About this role
Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future. If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match. About the position: Background Volvo Construction Equipment operates in a dynamic market environment influenced by economic conditions, customer demand, industry developments and other external factors. Within the Sales and Operations Planning, S&OP, process, different market development scenarios are used to support decisions related to demand, capacity, production, inventory and resource allocation. We are currently investigating methods to improve the quantitative assessment of market uncertainty in S&OP. In this thesis, the student will contribute by developing a methodology for estimating scenario probabilities and describing the relationship between different market development scenarios. Thesis Description The thesis will investigate how historical market projections, actual outcomes and potentially relevant internal and external indicators can be used to model market scenarios. The main objective is to develop and evaluate a data-driven approach for: • estimating the probability of baseline, upturn and downturn scenarios; • identifying factors that may explain deviations from the baseline; • establishing a statistical or mathematical relationship between the baseline and alternative scenarios; • evaluating the accuracy and reliability of the proposed methodology; • proposing how probabilistic scenario information could support the S&OP process. The exact scope will be defined together with the student and will depend on data availability. The study may focus on a selected market, region, product segment or business area. The task may include: • Reviewing relevant methods for probabilistic forecasting, scenario analysis and uncertainty modeling. • Defining quantitative criteria for baseline, upturn and downturn scenarios. • Preparing, structuring and analyzing historical projection and outcome data. • Investigating the relationship between projected and actual market development. • Developing and evaluating suitable statistical or machine learning models. • Estimating scenario probabilities and validating them against historical observations. • Proposing an approach for integrating the results into the S&OP process. • Presenting the results in a clear and practical format for business users. Potential methods may include regression, classification, time-series analysis, probabilistic forecasting, Bayesian modeling, Monte Carlo simulation and sensitivity analysis. Expected Background Applicants should meet the following requirements: • Be enrolled in a relevant master’s program at a university. • Have an interest in supply chain management, S&OP, forecasting, statistics, data science or operations research. • Have a solid understanding of probability and statistical analysis. • Be comfortable working with structured and time-series data. • Have experience with Python, R, MATLAB or a similar analytical programming environment. The project is suitable for students in fields such as: • Industrial Engineering; • Production Engineering; • Supply Chain Management; • Operations Research; • Statistics; • Applied Mathematics; • Data Science; • Economics or a related field. Applicants should be able to demonstrate relevant technical competence and an interest for statistical modeling, machine learning, data analysis or supply chain planning. The results may also include a data model, analytical tool or visualization to communicate market uncertainty to relevant stakeholders. Practical Information The thesis work comprises either 10 weeks of full-time study . The final duration and scope will be agreed upon with the selected student and the university. The student will collaborate with S&OP professionals and other relevant stakeholders at Volvo Group. A designated company contact person will be available throughout the thesis project to provide business context, discuss progress and support the student with questions related to the data and the S&OP process. The project should preferably be designed so that the results can be published. Depending on the data used, this may require aggregation, anonymization or transformation of confidential information. The final data scope and publication conditions will be agreed upon before the project starts. Company contact person: Claudemir Beneli Claudemir.beneli@volvo.com Romain Ferrand romain.ferrand.2@volvo.com Expected start date: tbd Expected end date: tbd Application deadline: tbd Important Prerequisite The final scope of the project depends on the availability and quality of historical market projections, actual outcomes and relevant explanatory data. The data availability and confidentiality conditions will be assessed before the thesis project is formally assigned. We value your data privacy and therefore do not accept applications via mail. Who we are and what we believe in We are committed to shaping the future landscape of efficient, safe, and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents across the group’s leading brands and entities. Applying to this job offers you the opportunity to join Volvo Group . Every day, you will be working with some of the sharpest and most creative brains in our field to be able to leave our society in better shape for the next generation. We are passionate about what we do, and we thrive on teamwork. We are almost 100,000 people united around the world by a culture of care, inclusiveness, and empowerment. Part of Volvo Group, Volvo Construction Equipment is a global company driven by our purpose to build the world we want to live in. Together we develop and deliver solutions for a cleaner, smarter, and more connected world. By unleashing everyone’s full potential, we build a more sustainable future for all our stakeholders. Come join our team and help us build a better tomorrow.