I am a Data Science leader specializing in machine learning, anomaly/outlier detection, and physics-based modeling, with domain experience across IoT and geospatial domains. I hold a Ph.D. in Ocean Physics from Columbia University and currently work at Nautilus Labs guiding our data science and machine learning engineering team to improve efficiency in the maritime industry.
My professional experience spans industry and academia, with common threads around robust statistical modeling, ocean/weather/climate system modeling, and the development of novel analytical approaches that often leverage data synthesis across domains. I additionally have experience developing robust, scalable, and observable data-transformation and model-training pipelines.
Drawing on my background as an educator, I strive for clear communication, statistically- and physically- supported models and analyses, and growing and supporting high-performing data teams.