Manufacturing Data Analytics Engineer: AI & Automation Lead

Allegro MicroSystems, LLC; Parañaque; On-site; PHP 1,000,000 - 2,000,000; Full time

Job summary

Allegro MicroSystems, LLC is seeking a data science professional to bridge semiconductor manufacturing and AI-enabled operations in Metro Manila. You will design end-to-end data-driven solutions, deploy predictive models, and drive digital transformation across production lines.

You will collaborate with cross-functional teams, manage data pipelines, dashboards, and model lifecycles, while ensuring cybersecurity and privacy compliance in a fast-paced environment.

Qualifications

• Bachelor’s or Master’s in Data Science, AI, CS, or Electrical/Electronics/CE.
• 3–5 years hands-on experience in automation, data analytics, and AI in semiconductor manufacturing.
• Proven ability to develop automated workflows and deploy AI systems into production.
• Experience integrating complex databases and cloud platforms.

Responsibilities

• Design and implement end-to-end data-driven solutions.
• Architect AI pipelines and integrate databases and cloud platforms.
• Lead digital transformation projects from inception to production.
• Collaborate with cross-functional teams and manage UAT/ deployment approvals.
• Sustain and document solutions, and develop training materials.

Skills

Data analysis

Machine learning

Automation workflows

Cloud integration

Education

Bachelor’s or Master’s in Data Science/Analytics/AI/CS/Engineering

3–5 years in automation/data analytics/AI in semiconductor manufacturing

Experience deploying AI in production

Experience integrating databases and cloud platforms

Tools

Python

SQL

TensorFlow

Azure

Job description

Allegro MicroSystems, LLC is seeking a data science professional to bridge semiconductor manufacturing and AI-enabled operations in Metro Manila. You will design end-to-end data-driven solutions, deploy predictive models, and drive digital transformation across production lines.

You will collaborate with cross-functional teams, manage data pipelines, dashboards, and model lifecycles, while ensuring cybersecurity and privacy compliance in a fast-paced environment.