Data Scientist, Machine Learning Engineer

NYU Grossman School of Medicine

Biography

I am a data scientist at NYU Grossman School of Medicine, specializing in education technology and learning analytics. With over 5 years of expertise, I excel in leveraging data to enhance analytics, extract insights, and design solutions. My focus spans diverse domains, but currently I am in the medical education sector.

My current focus is on developing and implementing MLOps for deploying and monitoring machine learning pipelines for experimentation and research. For th epast few years I have integrated end-to-end pipelines from notebooks into production code bases for feature processing and inference to predict note quality, screen medical school applications, and monitor student performance.

I am dedicated to delivering impactful actions that drive business metrics and inform leadership decisions. My foundation in applied statistics and quantitative modeling empowers me to collaborate effectively with cross-functional teams, offering insights into data collection, efficient processing, visualization, and automated reporting.

My commitment to problem-solving extends beyond education. Whether in healthcare or other fields, I thrive on utilizing data, statistics, and machine learning to tackle complex challenges.

Interests
  • Probabilistic Computation and Modeling
  • Machine Learning and Data Engineering
  • Music and guitar
Education
  • MSc in Applied Physics, 2017

    NYU Tandon School of Engineering

  • BSc in Physics, 2014

    Universidad de Los Andes, Colombia