Provide technical leadership to teams of data scientists and engineers;
Define analytical architecture and review implementations;
Ensure transparency, explainability, and reliability of models;
Design data and ML pipelines on Azure (ADF, Databricks, Azure Machine Learning);
Integrate models with APIs and real-time workflows;
Oversee the adoption of MLOps practices (MLflow, Kubernetes, Azure ML).
Requirements
Academic background: Degree in Information Technology or a mathematically based degree — Engineering, Statistics, Physics, or Mathematics; or a non-mathematical undergraduate degree with a postgraduate qualification in Information Technology;
Technical English knowledge preferred;
Experience in technical leadership on Data Science or Artificial Intelligence projects;
Strong experience as a Data Scientist, applying supervised and unsupervised learning techniques;
Participation in projects involving NLP, generative AI, embeddings, and semantic search;
Experience in model interpretation and explainability for machine learning;
Experience defining and overseeing complex analytical architectures with a focus on scalability, performance, and security;
Hands-on experience with data and ML pipelines using Azure Data Factory, Databricks, and Azure Machine Learning;
Proficiency in Python and SQL;
Experience with API integrations, large data volumes (real-time and batch), and MLOps tools (MLflow, Azure ML, Kubernetes).
Tech Stack
Azure
Kubernetes
Python
SQL
Benefits
Health plan: Hapvida, Bradesco or Unimed (according to regional collective bargaining agreement rates);
Dental plan: Hapvida Odonto or Bradesco Dental;
Meal or food allowance (Vale Alimentação or Refeição);