Amanda Miguel Austin

Amanda Miguel Austin is a seasoned data scientist with extensive experience in developing innovative data solutions and methodologies across various sectors. Currently serving as a Senior Data Scientist at Hitachi Solutions America, Amanda previously contributed to Steady, where notable projects included enhancing a job recommendation system with NLP, creating fraud detection methodologies, and conducting customer segmentation analysis. Amanda has also completed a Data Science Fellowship at Insight Data Science, focusing on predictive analytics for inventory management, and held a Postdoctoral Scholar position at Stanford University, contributing to microbiological research. Amanda's academic background includes a PhD and a Master's degree in Bioengineering from Stanford University, along with a Bachelor's degree from UC Merced.