Sr Manager, Industrial Engineering & Process Optimization

Twistbioscience; Portland (OR); On-site; USD 140,000 - 190,000; Full time

Job summary

Twist Bioscience seeks a Sr Manager, Process Optimization & Industrial Engineering to lead continuous improvement across high-throughput manufacturing. You will apply IE methods to diagnose bottlenecks, model capacity, and build data-driven cases for process redesigns, equipment investments, or staffing changes.

This onsite role in Wilsonville, OR requires 8–12+ years in IE, a track record of leading teams, and experience in ISO 13485 or GMP/GxP environments.

Qualifications

• Bachelor’s or Master’s degree in Industrial/Mechanical/Manufacturing Engineering or related field.
• 8–12+ years in industrial engineering, continuous improvement, or manufacturing process optimization.
• 3–5+ years in a supervisory, management, or cross-functional leadership role.
• Demonstrated hands-on experience in ISO 13485 or GxP-regulated environments.
• Strong analytical foundation with OEE, Cpk, takt time, and cost-per-unit modeling.
• Proven ability to influence cross-functional stakeholders without direct authority over manufacturing execution.
• Hands-on expertise using core industrial engineering tools (time-motion studies, line balancing, capacity modeling, value stream mapping).

Responsibilities

• Analyze manufacturing line performance data to identify capacity constraints, turnaround time bottlenecks, and labor utilization inefficiencies across production processes.
• Investigate first pass rate losses and defect trends; lead root cause analysis efforts with Quality and Manufacturing to reduce rework, scrap, and reprocessing.
• Develop and prioritize a pipeline of improvement opportunities, evaluating whether process redesign, equipment/automation investment, or staffing changes offer the best return.
• Build business cases and ROI models for proposed improvements, including capital equipment requests, to support engineering and manufacturing leadership decision-making.
• Design and implement process changes using industrial engineering tools (time-motion studies, line balancing, value stream mapping, DOE) and validate improvements through structured pilots.
• Partner with Automation Engineering to scope opportunities where equipment or automation upgrades can address capacity, quality, or labor constraints.
• Collaborate with Manufacturing and Workforce Planning to right-size staffing models and improve labor efficiency without compromising quality or compliance.
• Establish and track key performance indicators (OEE, first pass yield, cycle time, cost-per-unit) to measure the impact of improvement initiatives over time.
• Ensure all process changes are executed in compliance with GxP requirements, working with Quality Assurance on change control and documentation.
• Present improvement roadmaps, project status, and results to senior engineering and manufacturing leadership.

Skills

OEE analysis

Cpk analysis

takt time

value stream mapping

DOE

time-motion studies

line balancing

ROI modeling

root cause analysis

data-driven decision making

statistical process improvement

Education

Bachelor’s or Master’s degree in Industrial Engineering or related technical field

Job description

Sr Manager, Process Optimization & Industrial Engineering (onsite in Wilsonville, OR)

Job Description

The Sr. Manager of Industrial Engineering & Process Optimization will drive continuous improvement across high-throughput manufacturing operations by identifying, prioritizing, and executing initiatives that increase line capacity, reduce turnaround time, improve first pass rate, and optimize resource utilization. This role will apply industrial engineering methodologies—including time-motion studies, line balancing, capacity modeling, root cause analysis, and value stream mapping—to diagnose bottlenecks and quality losses across people, process, and equipment, and will develop data-driven business cases to determine whether the right solution is a process redesign, equipment/automation investment, or staffing model change. Reporting into the Engineering organization, this role will partner closely with Manufacturing leadership, Operations, Quality, and Automation Engineering to translate floor-level constraints into scalable, sustainable improvements, balancing near-term throughput gains with long-term operational excellence. The ideal candidate brings a strong analytical foundation (OEE, Cpk, takt time, first pass yield, cost-per-unit modeling), and experience operating in a Quality-regulated environment (including ISO 13485).

Key Responsibilities

• Analyze manufacturing line performance data to identify capacity constraints, turnaround time bottlenecks, and labor utilization inefficiencies across production processes
• Investigate first pass rate losses and defect trends; lead root cause analysis efforts in partnership with Quality and Manufacturing to reduce rework, scrap, and reprocessing
• Develop and prioritize a pipeline of improvement opportunities, evaluating whether process redesign, equipment/automation investment, or staffing changes offer the best return
• Build business cases and ROI models for proposed improvements, including capital equipment requests, to support engineering and manufacturing leadership decision-making
• Design and implement process changes using industrial engineering tools (time-motion studies, line balancing, value stream mapping, DOE) and validate improvements through structured pilots
• Partner with Automation Engineering to scope opportunities where equipment or automation upgrades can address capacity, quality, or labor constraints
• Collaborate with Manufacturing and Workforce Planning to right-size staffing models and improve labor efficiency without compromising quality or compliance
• Establish and track key performance indicators (OEE, first pass yield, cycle time, cost-per-unit) to measure the impact of improvement initiatives over time
• Ensure all process changes are executed in compliance with GxP requirements, working with Quality Assurance on change control and documentation
• Present improvement roadmaps, project status, and results to senior engineering and manufacturing leadership

What You’ll Bring to the Team

• Education: A Bachelor’s or Master’s degree in Industrial Engineering, Mechanical Engineering, Manufacturing Engineering, or a related technical field
• 8–12+ years of progressive experience in industrial engineering, continuous improvement, or manufacturing process optimization
• 3–5+ years in a supervisory, management, or cross-functional team leadership role
• Demonstrated hands‑on experience working within ISO 13485 or GxP-regulated environments.
• Strong analytical foundation with expertise in OEE, Cpk, takt time, and cost-per-unit modeling
• Proven ability to influence cross-functional stakeholders without direct authority over manufacturing execution
• Hands‑on expertise using core industrial engineering tools (time-motion studies, line balancing, capacity modeling, and value stream mapping)

Preferred Qualifications

• Experience working within high-throughput biomanufacturing, biotechnology, or life science manufacturing environments.
• Demonstrated track record of leading complex, multi‑functional process optimization or automation initiatives from diagnostic to execution.

About Twist Bioscience

Twist Bioscience synthesizes genes from scratch, known as “writing” DNA. Just as children learn to both read and write, the next phase of development for the genomics revolution is the ability to write DNA.

At Twist Bioscience, we work in service of people who are changing the world for the better. In fields such as health care, agriculture, industrial chemicals and data storage, our unique silicon‑based DNA Synthesis Platform provides precision at a scale that is otherwise unavailable to our customers.

Twist Bioscience Corporation is an Equal Opportunity Employer. Twist Bioscience Corporation provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic characteristics, or any other category protected by law.