Fangyuan Li
Helping businesses turn data into real-world impact. With 6+ years of experience in business intelligence, I build scalable data solutions that drive efficiency, innovation, and growth—across industries like manufacturing, healthcare, and cloud computing.
Featured Work
Here are a few projects that reflect my focus on data-driven transformation across Fortune 500 and tech-leading companies.
Amazon Web Services
GenAI Services Accelearator
I’m currently leading a cross-functional initiative to accelerate the deployment of GenAI products across AWS. To support this effort, I created a data tool that tracks the progress of individual solution architects and technical builders as they implement GenAI services for customers. The tool offers a comprehensive view of how GenAI deployment is progressing at the builder level—enabling leadership to coordinate efforts, identify momentum, and allocate support where it’s most needed. This initiative has already supported over 1,000 customers, helping the organization scale GenAI adoption more efficiently and deliver AI-driven solutions to the market at a faster pace.
Cloud Migration Monitoring Tool & Deployment Pattern Accelerator
Recognizing a major inefficiency in how cloud services were being deployed, I initiated and led the development of a cloud migration monitoring tool that detects stalled customer workflows and highlights accounts requiring immediate technical support. This tool gave solution architects and account teams clearer visibility into deployment progress, allowing them to proactively intervene and resolve bottlenecks. As a result, stalled time during cloud migrations was reduced by 20%, contributing to a 16% year-over-year increase in successful migration rollouts across North America.In collaboration with the builder team, we found that many customer requests shared similar needs—especially when deploying certain GenAI or cloud products. To help scale these efforts efficiently, I developed a tool that measures the impact of applying repeatable deployment patterns across customer implementations. The tool quantifies how using established approaches improves delivery speed and consistency, allowing builders to deploy services more effectively at scale. By making this impact visible, the tool helped promote broader adoption of the pattern-based model across teams—accelerating product rollout for thousands of customers.These tools not only streamlined internal processes but also enabled organizations across diverse industries to adopt advanced cloud infrastructure more quickly and effectively.
CVS Health
At CVS Health, I developed a data tool that transformed how the risk adjustment operations team accessed and used their data. Previously, the team struggled with fragmented and inconsistent information, often pulling reports manually from a mix of backend databases and Excel files. This made it difficult to generate timely insights or support cross-functional decision-making.To address this, I built automated 10+ ETL workflows that consolidated data from 6 different sources and supported the migration of reporting infrastructure to the cloud. This tool not only cleaned and standardized the data but also enabled more frequent refreshes—replacing static reports with timely, trusted insights.The new solution significantly reduced 90% of manual reporting overhead and gave the team the ability to perform deeper analysis based on fresh, integrated data. Stakeholders could now monitor campaign performance, track risk scores, and adjust strategies with greater speed and confidence. By introducing automation, cloud accessibility, and analytical flexibility, I empowered the team to shift from reactive reporting to proactive, data-informed operations—contributing to more efficient and accurate healthcare delivery.
Caterpillar
To help transform the company’s approach to data-driven decision-making in sourcing, I designed and implemented a machine learning model that analyzed historical pricing, usage patterns, and supplier data to identify components—such as tubes, seals, and gaskets—with the highest cost-saving potential. The tool surfaced over 100 components that had been previously overlooked, providing sourcing teams with clear, data-backed opportunities to renegotiate supplier contracts and optimize procurement. This project replaced manual guesswork with predictive analytics, enabling more strategic and efficient decision-making. The success of this initiative not only delivered measurable cost savings but also demonstrated how advanced data science could modernize legacy operations and drive enterprise-wide transformation in industrial manufacturing.
About
I’m a data professional passionate about solving real-world problems with scalable analytics solutions. My experience spans from manufacturing to cloud computing, with a strong focus on data engineering, machine learning, visualization and optimization. I hold certifications such as AWS Certified Database – Specialty, Advanced Google Analytics, Oracle Database Associate, Tableau Desktop Specialist, and I actively share insights through published technical content.
When I’m not working on the data, you’ll find me writing online articles, learning emerging technologies, or experimenting with GenAI tools.