Staff Data Scientist

Brazil

ABOUT THE ROLE 

The Staff Data Scientist on the Applied AI team is an experienced professional skilled at translating business opportunities into technical solutions using ML/AI modeling, statistical data analysis and experiment design. They are a hands-on developer, capable of driving initiatives from research to implementation of production-ready models. This role also involves acting as a bridge between stakeholders, facilitating understanding, and guiding pragmatic approaches to applying AI in different use cases, while advocating for data-informed decisions.

ABOUT THE TEAM

You will be part of our Applied AI team, the team responsible for framing strategic business problems leveraging AI solutions across VTEX. Alongside the team, you will lead efforts to frame, design, implement, deliver and measure Artificial Intelligence / Machine Learning / Data Science solutions towards the next level of VTEX products and seize strategic opportunities for our customers and business.

WHO YOU ARE

  • You have experience building ML pipelines using frameworks like Scikit-learn, PyTorch, Tensorflow or similar;
  • You are fluent in designing experiments with statistical rigor, such as A/B tests and data generation experiments;
  • You have experience handling big data for analysis, feature engineering and evaluating experiment results;
  • You understand differences between research and production-level code, in Python or similar;
  • You understand key requirements for deploying and maintaining ML/AI models in production environment;
  • You have strong communication skills, enabling you to simplify complex technical concepts into actionable insights, while effectively listening and learning from diverse points of view;
  • You enjoy collaboration, supporting colleagues and building products that customers love;

    Plus:
    • Experience in Search, Recommendation or Ads;
    • Experience applying LLMs using frameworks like LangChain, LangGraph, CrewAI, LlamaIndex or similar;
    • Experience in MLOps;
    • Experience developing low latency APIs.

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