Nick Petosa is an AI research scientist at Two Sigma with 11 years of experience applying deep learning to quantitative finance and real-world systems. A Georgia Tech MS and BS graduate with a perfect GPA, he has built production-ready ML tooling and research prototypes—from deep Q-learning trading agents and time-series classifiers to language-model fine-tuning and anomaly detection. His work spans both research and engineering: creating retrainable gradient-boosted pipelines, LSTM encoder-decoder models for data-to-text generation, and automated fraud-cluster classifiers deployed in large-scale environments. Based in New York, he blends academic rigor with hands-on implementation, often turning research ideas into packaged code and internal tools. Notably, his early projects include a published undergraduate contribution to quantum-chemistry infrastructure and mobile accessibility apps, showing a breadth that extends beyond finance-focused AI.
11 years of coding experience
9 years of employment as a software developer
Master of Science, Computer Science, Master of Science, Computer Science at Georgia Institute of Technology
Searching for freezing strategies that optimize transfer learning.
Contributions:42 commits, 2 PRs, 32 pushes in 2 months
transfer-learning
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