✦ Luna Orbit — AI & Machine Learning

Senior Data Scientist (AI Deployment)

at Braze

📍 São Paulo Onsite Posted March 19, 2026
Type Full-Time
Experience mid
Exp. Years 3-5+ years
Education Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field; Master’s or PhD preferred
Category AI & Machine Learning

This role involves developing and deploying AI models for BrazeAI, working with large datasets, and improving product capabilities through data pipelines and machine learning techniques.

  • Collaborate with customer analytics teams
  • Develop reusable data pipelines and APIs
  • Refine reinforcement learning algorithms
  • Contribute to product strategy with insights
  • Ensure successful adoption and measurable outcomes

The technical environment includes Python, TensorFlow, Keras, scikit-learn, SQL, cloud platforms like GCP, and container orchestration with Kubernetes, emphasizing scalable ML solutions.

The ideal candidate is a mid-level data scientist with 3+ years of experience in machine learning, data pipelines, and deployment, proficient in Python and cloud platforms. They should be capable of collaborating with technical teams and handling large-scale data environments.

PythonML libraries (TensorFlowKerasscikit-learn)SQLlarge-scale data experiencemodel deployment
DevOps toolsAirflowKubernetesTerraformGCP
GitCI/CDTensorFlowKerasscikit-learnAirflowKubernetesTerraformGCP
PythonTensorFlowKerasscikit-learnSQLML pipelinesmodel deploymentlarge-scale dataGCPKubernetesTerraformDevOps
PythonPandasTensorFlowKerasscikit-learnCatBoostXGBoostSQLML pipelinesmodel deployment
collaborationcommunicationproblem-solvingautonomyteamwork
Industry SaaS
Job Function Developing and deploying machine learning models for AI products
Role Subtype Data Scientist
Tech Domains Python, TensorFlow, Keras, scikit-learn, SQL / PostgreSQL, Google Cloud Platform
Data ScientistAI DeploymentPythonTensorFlowKerasscikit-learnSQLML pipelinesmodel deploymentlarge-scale dataGCPKubernetesTerraformDevOpsData ScienceMachine LearningAISaaSBig DataData Engineering

No experience with Python or ML libraries, Lack of large-scale data experience, No deployment or pipeline experience, Bachelor's degree not in relevant field

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