Raymond

Advanced Quality Engineer
MalePre-sales technical support/SolutionLive in United StatesNationality
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Work experience

  • Advanced Quality Engineer

    Dell Technologies
    2021.04-2024.09(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

    Tenaris
    2019.09-2020.05(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 Engineering
    2024.09-2025.12(a year)
  • University of California, Berkeley, US

    Mechanical Engineering
    2019.08-2020.05(10 months)
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