Daniel Wang
Software Engineer at Bloomberg LP
New Brunswick, New Jersey, United States
Summary
👤
Senior🎓
Top SchoolDaniel Wang is a software engineer with nine years of experience building reliable, production-facing systems and ML research tools, currently developing Bloomberg’s work-from-home platform used by thousands of employees weekly. He blends applied machine learning research—optimizing deep learning training memory and I/O during his MS at Princeton—with hands-on engineering, shipping CI/CD pipelines and remote-access portals at scale. His background spans full-stack and infrastructure work from cloud migrations and AWS CDK course labs to performance-tuned front-end and backend systems at startups and internships. Comfortable in both research and product environments, he’s contributed to open-source computational neuroscience tooling and taught information security labs, reflecting a practical curiosity for systems, infosec, and reproducible ML. Outside work he’s active in climate and effective altruism communities, and enjoys conversations at the intersection of ML, security, and global-impact solutions.
9 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Computer Science, summa cum laude, Bachelor's degree, Computer Science, summa cum laude at Princeton University
Spanish, Chinese
Github Skills (4)
modeling10
neuroscience10
python10
cognitive-science10
Programming languages (1)
Github contributions (5)
dcw3/security-learnings-journal
Jan 2022 - Feb 2023
Contributions:39 pushes, 1 branch in 1 year
dcw3/Thesis
Dec 2018 - Sep 2019
Contributions:21 pushes, 4 branches in 8 months
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