Summary
Alex Pollara is a data scientist with 11 years of experience who blends deep academic expertise in ocean engineering—culminating in a PhD on identifying vessels from passive acoustical data—with applied machine learning and signal processing work in finance and maritime security. Based in Hoboken, he currently develops natural language models for compliance and risk monitoring at UBS while maintaining ties to maritime systems research through a DHS-sponsored doctoral fellowship. His skill set spans DSP, image processing, anomaly detection, and pattern recognition, enabling cross-domain solutions that translate physical-sensor insights into robust data-driven models. Notably, his background in naval engineering and hands-on sea-trial experience gives him an uncommon ability to bridge real-world maritime phenomena with advanced analytics.
11 years of coding experience
Bachelor's degree, Naval Engineering, 3.31, Bachelor's degree, Naval Engineering, 3.31 at Stevens Institute of Technology