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Mid-level data scientist role in metro with generalist forecasting skills attracts many qualified applicants.
Retail forecasting and replenishment expertise creates high domain specificity and limited cross-industry transferability.
Explicit 3–6 years plus forecasting, Python, and domain experience create strict filtering.
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Provide daily demand forecasts and maintain forecasting configurations for a UK-based retail customer with a focus on accuracy and timeliness.
Analyze forecast performance and large retail and supply chain datasets to identify improvement opportunities and recommend corrective actions.
Automate forecasting processes using Python, Docker, and GitHub; support issue resolution and collaborate with engineering and product teams to improve forecasting systems.
Bachelor’s degree in Data Science, Statistics, Mathematics, Engineering, Supply Chain, Computer Science, or related field.
3–6 years of experience in demand forecasting, data science, supply chain analytics, or retail planning.
Hands-on experience with Python, Pandas, and data analysis techniques; experience with Docker and GitHub for code and deployment management.
Experience working in a customer-facing environment supporting forecasting or replenishment activities.
Experienced in demand planning and forecasting models within retail or supply chain domains, preferably supporting UK-based clients.
Technically skilled in Python programming, model monitoring, and automation of forecasting workflows.
Operationally capable of engaging directly with customers to interpret forecasting outputs and lead continuous improvement initiatives.