Analyze large, complex data sets related to demand forecasting, supply planning to uncover actionable insights
Apply statistical and machine learning techniques to forecast demand including data ingestion, data visualization and insights, verifying the integrity of data used for analysis
Implement optimization algorithms to improve supply chain efficiency, reduce costs, and enhance service levels
Serve as a subject matter expert (SME) for supply chain analytics, advising stakeholders on best practices, tools, and strategies for effective supply chain management
Identify inefficiencies within the supply chain and recommend data-driven strategies for continuous improvement

Bachelor’s or Master’s degree in Data Science, Computer Science, Industrial Engineering, Operations Research, Supply Chain Management, or a related field
10-15 years of experience in data science or Supply Chain Operations Analytics, or worked on forecasting projects leveraging statistical/ML models; experience with data visualization tools
Proficiency in data science tools and programming languages such as Python, R, SQL
Good, applied statistics skills, such as distributions, statistical testing, regression, etc
Hands-on experience with machine learning techniques/algorithms (e.g., regression, classification, clustering) and optimization models
Familiarity with supply chain processes such as demand forecasting, inventory management, procurement, logistics, and distribution
Strong problem-solving skills with the ability to analyze complex data sets and translate insights into actionable recommendations
Ability to work independently and as part of a team in a consulting environment
Excellent verbal and written communication skills to present findings clearly to non-technical stakeholders.

Staff Data Science Consultant – Supply Chain Operation Analytics

Key skills