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Open nowPosted today

GQ Ops IE Modeling and Automation Manager

MyCareersFuture97,045 open roles

Pay
SGD 8,000 – SGD 15,000 a month
Where
Central, Singapore
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Your applicationOpen nowGQ Ops IE Modeling and Automation ManagerMyCareersFuture · Central, Singapore

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8.1% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 3 days.

Share of postings closed within
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  2. 3.6%3 days
  3. 8.1%7 days
  4. 15.1%14 days
  5. 34.0%30 days
This job: posted today

MyCareersFuture median: 3 days open

The posting

As Manager, GQ Ops IE Modeling & Automation, you will lead the transformation of GQ Ops into a more automated, data-driven, and scalable operation. This role owns automation strategy, system enablement, IE modeling, planning tools, and data governance, with a strong focus on reducing manual touchpoints, improving operational reliability, and enabling a future-ready reliability lab operating model.

You will work closely with cross-functional teams—including GQ Ops, Process Engineering, Planning, IE, Central and Site Automation, IT, Facilities, and external partners—to identify high-impact opportunities, translate operational needs into practical solutions, and drive standardized, scalable execution across sites.

Key Responsibilities

1. Lab Automation Strategy & Deployment

  • Lead the GQ Ops automation roadmap to improve productivity, quality, safety, and operational consistency. W
  • Evaluate and benchmark industry solutions; translate relevant technologies into scalable lab automation strategies.
  • Drive equipment and process automation (e.g., laser mark, ALU, robotics, vision systems, workflow digitization) to reduce manual work.
  • Partner with stakeholders to define requirements, assess ROI, support vendor engagement, and execute FAT/SAT/PAC.
  • Standardize automation designs across sites based on best-known methods and operational needs.
  • Drive AI Transformation for speed, innovation and productivity.

2. MES & AMHS Enablement

  • Drive automation of key workflows and ensure MES readiness across development, UAT, deployment, and sustainment.
  • Enable AMHS integration to improve material flow, throughput, and system reliability.
  • Act as the central GQ Ops interface for MES, AMHS, and lab automation systems.
  • Partner with IT, Automation, and Operations teams to improve system uptime, performance, and issue resolution.
  • Support AMHS solutioning including layout optimization, tool interface readiness, and operational integration.

3. IE Modeling & Planning Systems

  • Develop and sustain scalable, automated planning systems to support GQ Ops operations.
  • Build IE models covering capacity, throughput, utilization (PeakUtil%), cycle time, and bottleneck analysis.
  • Translate business inputs (ramp plans, loading, tool availability) into actionable planning scenarios for decision-making.
  • Improve planning tool adoption, model accuracy, and cross-site standardization.
  • Develop digital tools, dashboards, and decision-support systems for operations.
  • Bridge the Plan-to-Performance (P2P) gap through modeling insights and feedback loops with operations teams.
  • Explore and deploy advanced analytics/AI use cases to improve prediction, automation, and decision quality.

4. MSH Greenfield Lab Enablement

  • Lead planning and enablement of MSH greenfield reliability lab for future ramp requirements.
  • Translate business needs into layout design, process flow, automation readiness, and execution plans.
  • Drive alignment on equipment selection, utilities, infrastructure readiness, and ODD requirements.
  • Coordinate across GEL, Process Engineering, Planning, Facilities, Automation, and vendors to ensure readiness and timelines.
  • Integrate automation, AMHS, MES, and data considerations early to ensure scalability and minimize rework.

5. Central Team Leadership & Cross-Site Execution

  • Lead and develop a high-performing central team.
  • Set priorities, manage deliverables, and ensure timely execution of automation and system initiatives.
  • Communicate insights clearly to stakeholders, including automation impact, system risks, and model outputs.
  • Drive cross-site alignment to standardize best-known methods and scale successful solutions.
  • Foster a culture of innovation, accountability, and data-driven decision-making.
  • Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
  • Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.

Minimum Requirement

  • Bachelor’s degree or higher in Industrial Engineering, Automation, Mechatronics, Electrical/Electronics, Mechanical Engineering, Computer Science, Data Science, or a related technical discipline.
  • Minimum 7 years of experience.
  • Relevant experience in automation, industrial engineering, manufacturing systems, planning, capacity modeling, data analytics, process improvement, or system implementation.
  • Strong working knowledge of MES, AMHS, equipment automation, and core operational metrics (capacity, throughput, cycle time, bottlenecks, and productivity).
  • Proficiency in data analysis and reporting tools such as Excel, SQL, Python, Power BI, Tableau, Power Platform, AI agent or equivalent.
  • Demonstrated ability to execute projects effectively, with strong communication, stakeholder management, and structured problem-solving skills.
  • Proven ability to collaborate across cross-functional and global teams, including GQ Ops, IE, Planning, Process Engineering, Automation, IT, Facilities, and external partners.

Preferred Qualifications

  • Experience in semiconductor manufacturing, backend operations, reliability labs, automation deployment, or high-volume manufacturing environments.
  • Hands-on experience with robotics, AMHS, MES integration, vision systems, auto-dispatching, workflow automation, or equipment integration.
  • Familiarity with industry automation standards and protocols (e.g., SECS/GEM, E84, E87, or similar interfaces).
  • Experience in ROI evaluation, vendor engagement, technical specification review, and FAT/SAT/PAC qualification processes.
  • Exposure to Industry 4.0, AI/ML applications, low-code automation platforms, or digital transformation initiatives.
  • Prior people management experience or demonstrated ability to lead, coach, and develop technical teams.
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