About

Melissa Fabros is a highly skilled Senior Machine Learning Engineer currently working at Disney. With over 10 years of relevant experience, she has developed expertise in a range of technical skills, including Python, Javascript, CSS3, HTML, Responsive Design, JQuery, Bootstrap, Version Control, SQL, SQLAlchemy, Flask, Node.js, React.js, D3.js, Jenkins, Travis CI, Elm, Django, Ruby, Git, PostGresQL, Pytest, Jasmine, Unittest, Mapbox, AWS, Jupyter Notebook, Jinga, Computer Vision, Shapely, Tifffile, CV2, Numpy, Pandas, Matplotlib, Python Image Library, Tmux, Keras, and Theano. Melissa has worked at various organizations, including Kiva and the National Science Foundation (NSF). During her time at Kiva, she gained experience in deploying machine learning models on AWS, building data pipelines, designing machine learning models in Tensorflow and Pytorch, mentoring data science practicum students, managing open-source development projects, moderating Kaggle competitions, providing data acquisition support to external academic researchers, and conducting research and experimentation with computer vision and NLP applications. At NSF, she served as a Principal Investigator for a 3-year grant that focused on multi-stakeholder fairness in recommender systems. Melissa holds a PhD candidate degree from the University of California, Berkeley, and has completed various certification programs, including Scrum Master Certification and a certificate in Hackbright Academy. She has also obtained degrees in English from the University of California, Riverside, and a certificate from the University of California. Overall, Melissa is a highly skilled and experienced Machine Learning Engineer with a strong background in software engineering and a passion for developing fair and ethical machine learning systems.