Supply Chain Data Scientist (Machine Learning & Optimization)
Overview / Summary: We are seeking a Data Scientist to design and develop machine learning and optimization models that improve supply chain operations. This role focuses on demand forecasting, inventory optimization, replenishment planning, predictive analytics, and operational optimization across supply chain functions.
Key Responsibilities:
Design and develop machine learning and optimization models to improve supply chain operations, including demand forecasting, inventory optimization, and replenishment planning.
Analyze large datasets from ERP, WMS, TMS, POS, and enterprise systems to identify operational inefficiencies and improvement opportunities.
Build predictive models and optimization algorithms for transportation, warehouse operations, workforce scheduling, and supply network planning.
Collaborate with business stakeholders, supply chain subject matter experts, and data engineers to translate business requirements into AI-driven solutions.
Deploy and monitor scalable machine learning solutions on cloud platforms.
Continuously improve key performance indicators, including service levels, inventory costs, and on-time delivery performance.
Required Qualifications:
Experience designing and developing machine learning and optimization models for supply chain operations.
Experience with demand forecasting, inventory optimization, and replenishment planning.
Ability to analyze large datasets from ERP, WMS, TMS, POS, and enterprise systems.
Experience building predictive models and optimization algorithms.
Ability to collaborate with business stakeholders, supply chain subject matter experts, and data engineers.
Experience deploying and monitoring scalable machine learning solutions on cloud platforms.
Ability to improve operational KPIs such as service levels, inventory costs, and on-time delivery performance.