Process Engineer(Pipeline Req)

Role summary

Key Responsibilities

• Provide technical support to internal clients (Production, Planning, Training, NPD, Clinical, etc.) as part of a Global Engineering Team.
• Partner with planning, software/validation, and business analytics teams to analyze, design, and implement improvements for current processes and digital tools.
• Deploy, maintain, and improve Standard Work; drive stability and scalability of core planning and production processes.
• Conduct studies to analyze root causes (Pareto, 5-Why, fishbone) and deliver feasible corrective and preventive actions.
• Plan, prioritize, and execute projects aligned with organizational goals; track benefits (productivity, lead time and inventory, cost, quality).
• Estimate manufacturing cost, determine standard times, and recommend tooling/process/automation requirements for new or existing product lines.
• Build dashboards and decision-support tools for capacity, inventory, and lead time management; maintain data sources and inputs with stakeholders.
• Perform business process and data analysis; proactively detect gaps and opportunities; convert insights into operational actions.
• Apply the DIKW model to transform raw data into actionable wisdom; clarify operational problems and deliver solutions for Treat Operations.
• Lead hypothesis-driven analyses using statistical modeling and machine learning to validate strategies and optimize operations (e.g., forecasting, anomaly detection, optimization).
• Develop and maintain decision support tools; present key findings to influence decision-making for cross-functional stakeholders.
• Influence and negotiate with global stakeholders to align requirements, timelines, and trade-offs; manage risks and facilitate change adoption.

• Works on problems of diverse scope where analysis of data requires evaluation of identifiable and ambiguous factors. Demonstrates sound judgment in selecting methods and techniques for obtaining solutions. Resolves a wide range of issues in creative, pragmatic ways, and networks with senior internal and external personnel in area(s) of expertise.

• A seasoned, experienced professional with a full understanding of process engineering, operations planning, and data science. Fully qualified, career‑oriented, and expected to independently contribute while influencing others through expertise and data.

• Structures and manages the execution of project/program tasks with general supervision and limited guidance; recommends new approaches; mentors junior engineers/analysts as needed.

Skills, Knowledge & Expertise

• Bachelor’s degree in Engineering, Industrial Engineering, Operations Research, Computer Science, or Data Science required; Master’s preferred.
• Typically 4–6 years of directly related experience in process/industrial engineering, operations planning, business analytics, data science, or manufacturing excellence.

• English: Fluent (must) for global negotiation/coordination. Japanese: Business level (preferred).

Benefits

• Standard Work, e.g., Lean, Six Sigma; root cause analysis; DOE/SPC; capability analysis.
• Advanced Excel, Power BI, and SQL for data extraction, transformation, and visualization; KPI design and dashboarding.
• Python or R for analytics and data science (e.g., pandas, NumPy, scikit‑learn/statsmodels, time‑series forecasting, optimization/OR).
• Experience building decision‑support tools for capacity, inventory, and lead time management; data quality and governance awareness.
• Basic knowledge of software development concepts and databases; familiarity with PHP, Java, or .NET is a plus.
• Basic project management (charter, schedule, risk/RAID, stakeholder management).