Rayoung Kwon
Data Analyst
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolRayoung Kwon is a data analyst with 10 years of experience who blends marketing analytics and hands-on engineering to turn ad data into actionable insights. Having led ad product planning and built automated performance dashboards and daily reports at A1 Performance Factory and Media&Art, she routinely integrates Google, Naver, Kakao, and Meta ad APIs with SQL, Python, Tableau and Figma workflows. Her background includes RFM and funnel analysis, VOC collection, and advertiser-focused dashboarding for verticals like insurance and cosmetics. Beyond marketing, she contributes to high-performance graphics and ML projects—implementing Vulkan renderer features in the bgfx library and improving MNN’s Vulkan backend—reflecting deep low-level systems skills not typical for a marketing analyst. Based in Seoul, she pairs multidisciplinary academic training in big data convergence and media/communication with a practical knack for turning complex logs into business-facing products.
10 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Interior Architecture & Built Environment, 3.53/4.3, Bachelor of Science - BS, Interior Architecture & Built Environment, 3.53/4.3 at Yonsei University 연세대학교Master of Arts - MA, Broadcasting · Visual Communication · Culture Contents, 3.98/4.3, Master of Arts - MA, Broadcasting · Visual Communication · Culture Contents, 3.98/4.3 at Yonsei University Graduate School of Journalism, Media and CommunicationBusan Science High SchoolMaster of Engineering - MEng, Big Data Convergence, Master of Engineering - MEng, Big Data Convergence at Korea University Graduate School of SW·Al ConvergenceBachelor of Communication, Communication, 3.53/4.3, Bachelor of Communication, Communication, 3.53/4.3 at Yonsei University
Github Skills (18)
vulkan10
c-language10
rendering10
machine-learning10
render10
graphic10
deep-learning10
cprogramming-language10
multiplatform9
cross-platform9
platform-independent9
arm8
convolution8
opengl7
metal5
Programming languages (4)
Github contributions (5)
alibaba/MNN
Aug 2020 - Aug 2020
MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba. Full multimodal LLM Android App:[MNN-LLM-Android](./apps/Android/MnnLlmChat/README.md)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 reviews, 12 commits, 1 PR in 14 days
Contributions summary:Rayoung primarily contributed to the MNN deep learning framework, focusing on improving the converter tool and Vulkan backend. Their work includes implementing PRelu conversion for TFLITE framework and addressing issues in the Vulkan backend, such as image layout and buffer mapping. They also made improvements to the Vulkan image and buffer handling within the framework. These commits highlight their work in optimizing the Vulkan backend and expanding the converter's capabilities.
casesvulkanconvolutionalibabaframework-learning
bkaradzic/bgfx
Jul 2019 - Aug 2019
Cross-platform, graphics API agnostic, "Bring Your Own Engine/Framework" style rendering library.
Role in this project:Graphics & Rendering Engineer
Graphics & Rendering EngineerContributions:10 commits, 9 PRs, 42 comments in 1 month
Contributions summary:Rayoung implemented significant portions of a Vulkan renderer within the bgfx graphics library. Their work focused on core features, including image memory barrier implementations, render pass creation, and frame buffer integration. Key contributions involved setting up swapchain functionality and addressing platform-specific considerations, as evident in the inclusion of macOS support. Further improvements included sampler caching and support for blitting, debug drawing, and instancing.
metalbgfxvulkanvulkan-apiagnostic
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