June Oh
Global Client Director at LinkedIn
Seoul, Singapore
Summary
🤩
Rockstar🎓
Top SchoolJune Oh is a Global Client Director based in Seoul with 10 years of experience driving strategic partnerships and revenue growth across APAC for major digital platforms, currently leading global partnerships at LinkedIn. She combines enterprise account leadership and go-to-market expertise honed through progressive roles at MediaMath—where she led platform solutions, regional account development, and APAC business development—with an MBA from Columbia Business School. Fluent in bridging marketing, programmatic ad tech and client strategy, she also brings hands-on ML and cloud tooling experience from open-source work on preconfigured TensorFlow Docker environments, improving usability for model development. Known for operating at the intersection of sales, product and technical enablement, she excels at turning complex technical capabilities into client-ready solutions across diverse Asian markets.
10 years of coding experience
8 years of employment as a software developer
BS Advertising (Interactive/Digital Media) Economics & Spanish, BS Advertising (Interactive/Digital Media) Economics & Spanish at The University of Texas at AustinMaster of Business Administration (M.B.A.), Master of Business Administration (M.B.A.) at Columbia Business SchoolEconomics, Economics at Universidad Complutense de Madrid
English, Korean, Spanish, Japanese
Github Skills (8)
conda10
docker10
tensorflow10
dockers10
python9
cuda9
jupyter8
ubuntu7
Programming languages (11)
Github contributions (5)
deeplearningzerotoall/TensorFlow
Oct 2018 - Apr 2019
Deep Learning Zero to All - Tensorflow
Role in this project:
DevOps Engineer
DevOps EngineerContributions:5 commits, 1 PR, 3 pushes in 5 months
Contributions summary:June primarily focused on building and maintaining Docker images for the TensorFlow project. Their contributions included creating and updating Dockerfiles for various TensorFlow versions, including those with CUDA support. They added necessary dependencies, configured the environment (including Python and Conda), and set the default command to run a Jupyter notebook. This work improved the project's usability by providing pre-configured environments for running TensorFlow models.
deep-learningtensorflow
juneoh/dotfiles
Mar 2017 - May 2020
Contributions:80 commits, 43 pushes, 3 branches in 3 years 2 months
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