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Refactor and enhance existing optimization algorithms written in Python using object-oriented programming principles.
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Apply advanced data science techniques to solve business problems in supply chain optimization and retail/CPG inventory planning.
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Analyze large and complex datasets using statistical methods and machine learning models to generate insights for replenishment and inventory allocation.
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Develop, deploy, and maintain predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource utilization.
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Collaborate with cross-functional teams to translate business requirements into scalable, data-driven solutions.
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Design and execute experiments to assess the effectiveness of replenishment strategies and allocation policies.
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Monitor key supply chain performance metrics, evaluate model performance, and make recommendations for continuous improvement.
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Stay updated on industry trends, tools, and best practices in data science, optimization, and supply chain management.
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Mentor and collaborate with other data scientists to promote knowledge sharing and skill development.