Data Science (2089)

Job Description The ideal candidate will use data driven insights to improve supply chain performance enable better decision making and solve operational challenges. This role works closely with cross functional teams and applies advanced analytics machine learning and optimization techniques across supply chain areas such as forecasting planning and process improvement. What You’ll Do • Data Analysis & Modeling: Work with large supply chain datasets (demand supply inventory) to identify trends and actionable insights. • Machine Learning for Forecasting: o Apply and refine statistical/ML-based forecasting models o Perform data ingestion cleaning validation visualization and feature engineering configuring forecasting models o Tune and evaluate forecasting models o Communicate insights clearly to stakeholders • Supply Chain Optimization: Apply optimization models/algorithms to improve efficiency reduce costs and improve service levels. • Consulting & Advisory: Act as an analytics SME guiding teams on best practices tools and data-driven decision approaches. • Process Improvement: Identify gaps in supply chain processes and recommend data-backed improvements. What We Are Looking For • Education: Bachelor’s or Master’s degree in Data Science Computer Science Industrial Engineering Operations Research Supply Chain or related fields. • Experience: 6–18 years in data science or supply chain analytics with strong exposure to forecasting statistical/ML modeling or supply chain planning analytics. • Technical Skills: o Proficiency in Python/R/SQL o Strong applied statistics (distributions hypothesis testing regression) o Experience with data visualization tools o Experience with supply chain data planning systems or forecasting processes • Machine Learning: Hands-on experience with regression classification clustering or optimization algorithms. • Industry Knowledge: Understanding of demand forecasting inventory planning procurement logistics or related supply chain functions. • Analytical Skills: Ability to work with complex datasets and convert findings into practical business recommendations. • Personal Competencies o Ability to work independently and collaboratively in a consulting environment. o Strong attention to detail with comfort handling large datasets. o Excellent verbal and written communication skills to simplify technical insights for non technical teams.