Remote Lead Data Scientist - Replenishment Optimization

Description:

• The Lead Data Scientist will be responsible for refactoring the Distribution Optimization algorithm using Object Oriented Programming in Python.
• They will work on applying data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG.
• Analyze large datasets using advanced statistical techniques and data science algorithms to derive insights related to replenishment optimization and inventory allocation.
• Develop and implement predictive models and optimization algorithms to enhance inventory management, reduce stockouts, and optimize resource allocation in the supply chain.
• Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
• Design experiments to evaluate different replenishment strategies and allocation policies' effectiveness.
• Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, providing recommendations for improvement.
• Stay updated on industry trends in data science, replenishment optimization, and supply chain management to drive innovation.
• Collaborate, coach, and learn with a team of experienced Data Scientists.

Requirements:

• Minimum 6 years of experience as a Data Scientist, focusing on replenishment optimization and inventory allocation.
• Bachelor's or Master's degree in Computer Science, Statistics, Operations Research, or a related field.
• Proficiency in Python, Pyspark, and SQL, with experience in data analysis and machine learning libraries.
• Strong understanding of statistical methods, optimization techniques, and predictive modeling concepts.
• Ability to apply analytical models to business use cases.
• Excellent communication and collaboration skills to understand business partner needs and deliver solutions to stakeholders.

Benefits:

• Significant career development opportunities in a fast-growing and challenging entrepreneurial environment.
• High degree of individual responsibility in the role.