ML/AI - Supply Chain

What you'll do

• Set the supply chain AI transformation roadmap and collaborate with executive and cross-functional stakeholders.
• Design, deploy, and monitor production ML models and data pipelines for forecasting, optimization, risk scoring, and anomaly detection.
• Establish modeling, MLOps, governance, and adoption practices; mentor junior scientists and support supply chain teams.

What they ask for

• 8+ years in applied data science or ML; supply chain, operations research, logistics, or manufacturing experience is described as ideal.
• Master's or PhD in Computer Science, Statistics, Data Science, EE, OR, or a related technical field.
• Strong Python and SQL; production ML development and deployment experience, including MLOps and real-time inference pipelines.
• Expertise in statistical modeling and ML, including time series forecasting, optimization, anomaly detection, and causal inference.

Nice to have

• Experience with experiments, Bayesian methods, advanced forecasting, model compression, or multi-region inference.
• Supply chain and ERP expertise; experience with consumer electronics or B2B hardware manufacturing.

Pay

$178,640 — $319,000 USD (annual base salary)

Tools

Python, SQL, Tableau, Power BI, AWS, GCP, Azure, NetSuite

AI focus

Apply AI/ML to supply chain transformation, including demand and inventory forecasting, supplier risk scoring, spend prediction, cost optimization, and anomaly detection using ERP, IoT, and third-party data.