
Huy Pham
@huypham6120
Data center operations pro (99.99% uptime) applying data analytics to reliability — advancing into data engineering & ML.
What I'm looking for
Technology and operations professional bridging live infrastructure with data engineering and applied machine learning.
At GDS (Global Data Service), I monitor Tier III data center infrastructure and coordinate incident response across network, facility, and customer-support teams to sustain 99.99% service availability across colocation, hosting, and connectivity operations. I built and maintain an automated operational-health checklist that improved early anomaly detection and cut time-to-visibility on abnormal conditions.
My foundation is dual Purdue University degrees in Data Science and Supply Chain Information & Analytics. As an undergraduate researcher, I processed and cleaned 16M+ data points from a legacy system for ML deployment, surfaced supplier-performance insights from 400K+ records, and built a forecasting model that explained 65% of variance in delivery timelines — 30% above baseline. I hold certifications in Google Cloud Data Analytics, Google Advanced Data Analytics, AWS, and Power BI.
I'm now building toward data engineering and applied ML — pairing hands-on infrastructure reliability experience with a data-first approach to automation and business performance.
Experience
Work history, roles, and key accomplishments
• Monitor Tier III data center infrastructure and service performance through centralized alerting and ticketing systems to detect, escalate, and mitigate potential disruptions proactively.
• Coordinate cross-functional incident response between network, facility, and customer-support teams to resolve issues under strict SLA commitments and support 99.99% service availability across colocation, ho
• Led preprocessing of 16 million data points from a legacy system, ensuring quality and readiness for feature engineering and machine learning deployment.
• Analyzed 400,000 data points to to identify top and underperforming suppliers, driving insights to enhance supply chain reliability.
• Optimized a Machine Learning model explaining 65% of variance in suppliers' delivery timelines, outperformi
• Led a team in preprocessing 36,000 data points to uncover key trends and develop forecasting models at Purdue University.
• Researched and applied ARIMA models, resulting in a 20% improvement in forecasting accuracy for market trend predictions.
• Conducted functionality testing for 20+ website URLs and created 10+ redirect links daily to ensure seamless customer access.
• Developed 15+ comprehensive analysis reports for websites using Google Ads and Shopify data, resulting in a 20% increase in customer engagement.
• Preprocessed and optimzed over 200,000 data points for a $2 million ERP project, enhancing accuracy and enabling seamless integration.
• Developed 7 detailed Tableau dashboards with drill-down views for stakeholders to uncover actionable insights efficiently.
• Collaborated with at least 10 other student associates per shift to ensure smooth operations at multiple food stations, enhancing efficiency and meeting customer's demands.
• Maintained detailed logs for food safety standards for up to 3 stations per shift, ensuring quality and temperature compliance.
Education
Degrees, certifications, and relevant coursework
Purdue University
Bachelor of Science - BS, Computer Science
2018 - 2024
Major: Data Science
Purdue University Daniels School of Business
Bachelor of Science - BS, Supply Chain Information & Analytics
2018 - 2024
Concentration: Management Information Systems
Microsoft
Microsoft Power BI Data Analyst
Google Advanced Data Analytics
Amazon Web Services
AWS Fundamentals: Your First Steps into the Amazon Cloud
Google Cloud
Google Cloud Data Analytics
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Social media
Job categories
Skills
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