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Bayan Lepas
Dashine Nair Vasu

Dashine Nair Vasu

Ops Data Analyst & Process Eng Lead

Manufacturing / Mechanical

Bayan Lepas, Pulau Pinang

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About Dashine Nair Vasu:

Process and Operations Analytics professional with 8 years of
experience across manufacturing, facilities, and equipment-intensive
environments. Strong background in analyzing operational and
process data to identify trends, performance gaps, and improvement
opportunities. Six Sigma Green Belt, Professional Technologist (Ts.)
under MBOT, and Graduate Engineer (GE) under BEM. Experienced in
translating complex engineering and operational challenges into
structured, data-driven insights, dashboards, and actionable
recommendations through cross-functional collaboration.

Experience

Process and Operations Analytics professional with 8+ years of experience across manufacturing, facilities, and equipment-intensive environments. Proven track record in analyzing operational and process data to identify performance gaps, optimize processes, and support data-driven decision-making. Strong background in manufacturing analytics, KPI and yield analysis, incident and downtime trending, and statistical validation using Six Sigma methodologies. Experienced in translating complex engineering challenges into structured insights, dashboards, and actionable recommendations through cross-functional collaboration. Brings a unique blend of process engineering leadership and analytics to drive efficiency, quality, and scalability in manufacturing and technology-driven organizations.

Education

Master of Engineering Management, complemented by a Bachelor’s degree in Chemical & Environmental Engineering, providing a strong foundation in engineering principles, operations management, and data-driven decision-making. Completed formal training in Power BI for data visualization and dashboard development, and certified Lean Six Sigma Green Belt. Well-versed in process and quality tools including PFMEA, EFMEA, GR&R, SPC, and process capability analysis to support structured operational and manufacturing analytics.

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