AI Engineer for Supply Chain Data Analysis

PEOPLEBANK SINGAPORE PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

PEOPLEBANK SINGAPORE PTE. LTD. is seeking a proficient AI/ML Specialist to develop models for supply chain analytics and decision support. The role involves designing data pipelines, feature engineering, and predictive analytics to enhance logistics performance.

You will collaborate with domain experts and engineers, evaluate model performance, and publish results where applicable. A strong emphasis on integrating AI with enterprise systems and cloud platforms is expected.

Responsibilities

• Develop AI and machine learning models for supply chain and logistics data analysis, forecasting, and decision support.
• Design and implement data pipelines, feature engineering, and predictive analytics models to improve supply chain performance.
• Develop optimization algorithms for logistics planning, routing, fleet management, inventory optimization, and resource allocation.
• Integrate AI models with enterprise systems and cloud-based data platforms.
• Evaluate model performance, conduct experiments, and continuously improve AI models based on operational data.
• Collaborate with domain experts, software engineers, and business stakeholders to translate operational requirements into AI-driven solutions.
• Prepare technical documentation, reports, and presentations, and contribute to scientific publications where applicable.
• Stay up to date with the latest advances in artificial intelligence, machine learning, and supply chain analytics technologies.

Skills

AI/ML

Forecasting

Data analysis

Optimization

Feature engineering

Data pipelines

Job description

• Develop AI and machine learning models for supply chain and logistics data analysis, forecasting, and decision support.


• Design and implement data pipelines, feature engineering, and predictive analytics models to improve supply chain performance.


• Develop optimization algorithms for logistics planning, routing, fleet management, inventory optimization, and resource allocation.


• Integrate AI models with enterprise systems and cloud-based data platforms.


• Evaluate model performance, conduct experiments, and continuously improve AI models based on operational data.


• Collaborate with domain experts, software engineers, and business stakeholders to translate operational requirements into AI-driven solutions.


• Prepare technical documentation, reports, and presentations, and contribute to scientific publications where applicable.


• Stay up to date with the latest advances in artificial intelligence, machine learning, and supply chain analytics technologies.