Caitlon Vu

Supported T-Mobile’s T-Life app monetization team by delivering data products, insights, and metrics that drive digital product health monitoring, informed release planning, and data-driven decision-making.

• Developed and owned 8+ end-to-end BI dashboards to monitor digital product health, user engagement, and monetization performance for the T-Life mobile app and T-Mobile web.
• Partnered closely with product managers to translate business requirements into actionable reports.
• Defined and implemented 20+ KPIs per feature to monitor monthly app releases, helping identify performance issues pre-launch and reducing defects by 12%.
• Automated data pipelines and reporting workflows using Snowflake and Power BI data flows to improve data operations and reduce manual reporting time by 10 hours per month.
• Conducted deep-dives on customer behavior, feature adoption, and revenue drivers, generating insights that helped direct product roadmap decisions.
• Led a cross-functional task force of engineers, QA analysts, and marketing partners to align on experiment design, success metrics, and outcome analysis, ensuring actions were taken according to test results.
• Presented findings and recommendations to leadership, enabling strategies and product enhancements.

Performed exploratory data analysis that drives visibility to problems in production using SQL, Excel, R, and Python and transformed complex datasets into dashboards and data visualizations using Power BI.

• Developed report KPI metrics to track and understand business performance in a large organization and fast-paced environment.
• Created statistical models to identify key factors in production line performance, utilizing regression analysis and data visualization techniques to drive efficient improvements.
• Maintained a portfolio of >100 robust intelligence reports to support data-driven decisions.
• Proactively identified and resolved data discrepancies, enhancing data quality and reliability, which resulted in improved accuracy and trust in reporting.
• Presented reports to executive audiences and made actionable recommendations leveraging evidence from data trends.
• Consulted with customers on gathering requirements and understanding business applications. Translate requirements into clear, comprehendible reports to fit customers’ dynamic needs.
• Facilitated continuous customer feedback on improving data accuracy and interpretation.
• Coached peers on technical skills and data analysis methods, empowering colleagues to take on complex analytical tasks.
• Conducted weekly office hours to provide insights and knowledge sharing with stakeholders and peers, driving informed decision-making and fostering a culture of continuous learning.

Drove lean manufacturing excellence by implementing solutions to improve output, quality, utilization, and overall factory effectiveness to reach weekly and quarterly goals.

• Spearheaded the successful migration of factory operations from an outdated tracking system to a new Manufacturing Execution System (MES), enhancing real-time accuracy and operational efficiency, improving overall productivity.
• Led a cross-functional team through the entire project lifecycle from project definition to final delivery to successfully launch a new factory line.
• Built and maintained reports to help management make enhanced data-driven decisions.
• Developed and maintained manufacturing systems and applications such as MES, dispatches, factory alert notifications, global factory prioritization, incoming material tracking, line health and critical factory indicators for 5+ factory modules.
• Led the integration of new product introductions, optimizing manufacturing processes to ensure seamless compatibility with existing products.
• Collaborated with international factory partners to plan production schedules, optimizing output and capacity utilization for the business.
• Took ownership of manufacturing collateral models and ensuring the supply chain is healthy. Make long-range purchasing decisions based on forecasted projections.
• Initiated and completed labor reduction projects, reducing computer tasks by 1000 hours per year by automating previously manual tasks.