Working closely with cross-functional stakeholders, you will leverage statistical modelling, machine learning, and predictive analytics to improve forecasting accuracy, optimise inventory, and drive operational efficiency. Apply statistical modelling and machine learning techniques to address supply chain challenges, including demand forecasting, inventory optimisation, and replenishment planning. Develop, test, validate, and deploy predictive models using robust statistical methodologies, including regression analysis, time series forecasting, and Bayesian approaches. Partner with supply chain stakeholders, including demand planners and inventory managers, to translate business requirements into actionable analytical solutions. Analyse large and complex datasets to uncover insights that improve service levels, reduce costs, and optimise inventory performance. Contribute to the design and development of scalable data science solutions within cloud-based environments such as Databricks and Azure. Present findings, insights, and recommendations clearly to both technical and non-technical audiences. Support the ongoing development and advancement of data science capabilities across the organisation. Master's degree in Statistics, Econometrics, Mathematics, or a related quantitative discipline. Minimum of 4 years' experience in a Data Science, Advanced Analytics, or similar role. Experience applying analytics within a supply chain environment. Ability to collaborate effectively within cross-functional teams.
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