Data scientists who apply statistical and ML techniques to extract insights from data.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Using data and metrics to measure performance, run experiments, and inform decisions.

Building, training, and deploying machine learning models — from classical ML to deep learning.

Using AI coding assistants and tools to write, review, and ship code faster.

Use AI to accelerate data science work while producing analysis you can validate, explain, reproduce, and defend.

Director of AI | Ex-Microsoft, IBM

Gabriela de Queiroz