Senior Data Scientist
Andrew Tseng is a senior data scientist at SFL Scientific with an expertise in developing computer vision (CV) and natural language processing (NLP) applications for S&P 500 clients. Andrew works with financial services, media, and retail organizations to develop AI-based solutions for operations, document management, and other R&D applications using deep learning for CV, transformer-based models, and time-series analysis.
Prior to joining SFL Scientific, Andrew worked for the Booz Allen Hamilton subsidiary, Modzy, as a research data scientist in AI Explainability. Andrew gained hands-on experience across all AI modalities, with a focus in drift detection for production level, machine learning applications. In 2021, Andrew’s research was presented at the 2021 NVIDIA GTC Conference and published at the 2021 CVPR summit, regarded as one of the most important conferences in the computer vision and pattern recognition field. Andrew Tseng earned his Master’s Degrees in Computer Science from the Goeriga Institute of Technology and Civil Engineering from the National Cheng Kung University in Taiwan, where his studies focused on the development of GPU-based parallel computing systems for large-scale multi-body systems.