Raymond
Advanced Quality Engineer
MalePre-sales technical support/SolutionLive in United StatesNationality
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Work experience
Advanced Quality Engineer
Dell Technologies2021.04-2024.09(3 years)⚫ Managed end-to-end quality programs for all Precision 3000 series workstation (1M+ shipments per year) in product development cycle from NPI to EOL and implemented continuous quality improvement, saving $2M in repair costs. ⚫ Led successful launch of 11 NPI platforms (Desktop / Workstation), achieving less than 0.1% RMA rate in 3 months. ⚫ Collaborated with cross-functional program teams and ODMs to resolve 100+ issues using Root Cause Analysis, pareto analysis, DOE, and 8D reports to prevent recurrence and optimize overall product performance ⚫ Managed risk assessments, trade-off decisions, and mitigation plan to balance quality objectives, schedule and cost. ⚫ Directed field failure analysis (FA) across diverse ME/EE/SW components, driving ODMs and internal engineering teams to identify root causes and implement Closed Loop Corrective Action to secure long-term product reliability." ⚫ Expanded program scope by managing high-impact product quality escalations, orchestrating cross-functional rapid response teams to define containment strategies and mitigate global field exposure ⚫ Designed and maintained automated Power BI + SQL quality analytics platform, replacing manual spreadsheet reviews and increasing issue detection efficiency by 40% across 5 product lines. ⚫ Drove quality improvements by eliminating sources of defects in the design, supplier, and manufacturing process. ⚫ Directed ODMs to conduct comprehensive NUDD analysis, critically reviewing and approving Product Quality Plans (PQP) to ensure strict adherence to design standards and risk mitigation prior to mass production.Machine Learning Engineer Intern
Tenaris2019.09-2020.05(9 months)⚫ Utilized Python / SQL to perform a multitude of analysis testing on array of piping that is used in the Oil and Gas industry for offshore and onshore well drilling. ⚫ Implemented Random Forest models with Bootstrap resampling and feature engineering to predict wellbore and drilling process quality, achieving 86% prediction accuracy and saving company 28% in inspection and drilling budget. ⚫ Classified the quality of over 100 wellbores, processing more than 1 million data points to support the introduction of a new company-wide data initiative
Educational experience
University of California, Irvine, US
Software Engineering2024.09-2025.12(a year)University of California, Berkeley, US
Mechanical Engineering2019.08-2020.05(10 months)
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