Global Turnaround Scheduler SME — Lead Readiness & FEL

Dow Inc.; Bridge City (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive pay

Annual bonus

Healthcare

Training programs

Job summary

Dow Inc. is seeking a Global Turnaround Scheduler SME in the Gulf Coast region to provide global scheduling expertise and governance across the Platinum work process. You will partner with site teams, leadership, and functional stakeholders to ensure adherence to standards and improve turnaround outcomes.

The role emphasizes coaching, assurance activities, and performance oversight to elevate scheduling competitiveness and predictability during FEL and execution phases.

Qualifications

• Bachelor's degree with 5+ years in turnaround execution or 10 years in lieu of degree.
• Deep knowledge of Primavera and scheduling processes.
• Experience as master scheduler in major turnarounds preferred.
• Willing to travel up to 25% domestically and internationally.

Responsibilities

• Own and govern global turnaround scheduling discipline and governance.
• Provide scheduling leadership for major turnarounds to improve readiness.
• Assess readiness, risks, gaps, and drive improvement actions.
• Lead readiness reviews, gate reviews and challenge sessions.
• Develop training curriculum and mentor schedulers globally.

Skills

Front-End Loading (FEL)

Risk Management

Leadership

Communication

Stakeholder Management

Facilitation

Cross-Functional Collaboration

Education

Bachelor's degree

5+ years turnaround experience

Tools

Primavera

Scheduling software

Job description

Dow Inc. is seeking a Global Turnaround Scheduler SME in the Gulf Coast region to provide global scheduling expertise and governance across the Platinum work process. You will partner with site teams, leadership, and functional stakeholders to ensure adherence to standards and improve turnaround outcomes.

The role emphasizes coaching, assurance activities, and performance oversight to elevate scheduling competitiveness and predictability during FEL and execution phases.