Priscilla Moraes
Group Data Science Manager
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolPriscilla Moraes is a Group Data Science Manager at Microsoft with 14 years of experience building and scaling AI and ML solutions across cloud platforms, specializing in responsible AI, governance, and production-grade MLOps. She previously led Google Cloud’s global ML and AI learning portfolio and created hands-on training and Advanced Solutions Lab curricula, blending technical depth with educator instincts. Her hands-on background includes ML engineering contributions to popular Google Cloud training labs (e.g., a Keras/tf.data classification lab in the training-data-analyst repo) and performance work on ONNX Runtime to accelerate customer deployments. Comfortable moving between strategy, team leadership, and code, she pairs a PhD in Computer and Information Science with recent executive training at Stanford GSB. Based in Austin, she brings rare cross-industry experience—from accessibility-focused NLP at IBM to academic teaching and research—that informs pragmatic, ethically minded AI productization.
14 years of coding experience
13 years of employment as a software developer
Organizational Leadership, Organizational Leadership at Stanford University Graduate School of BusinessMS Computer Science, MS Computer Science at Universidade SalvadorPhD Computer and Information Science, PhD Computer and Information Science at University of Delaware
Portuguese, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (5)
keras10
tensorflow10
python9
machine-learning9
data-preprocessing9
Programming languages (2)
Github contributions (5)
GoogleCloudPlatform/training-data-analyst
Apr 2020 - Mar 2021
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 79 commits, 78 PRs in 10 months
Contributions summary:Priscilla contributed to the development of a machine learning model within the context of the training-data-analyst repository, specifically focused on a classification model for wine production quality. Their primary contribution involved creating an introductory lab utilizing the Keras Sequential API and the tf.data API for creating input pipelines. The user's code changes demonstrate an understanding of data cleaning, inspection, dataset splitting, and model definition using the Keras Sequential API.
gcpgoogle-cloud-platformgoogle-cloudtraining
priumoraes/bluemix-python-flask-sample
Apr 2016 - May 2016
Contributions:2 PRs, 14 pushes in 17 days
pythonmicroframeworkflaskpython-flaskbluemix
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