Forward-deployed Data Scientist

Braze Braze · Enterprise · Tokyo, Japan · Customer Experience

This role focuses on designing and building end-to-end machine learning solutions for 1-to-1 personalization, with a strong emphasis on Reinforcement Learning (RL) use cases. The Data Scientist will own the full ML pipeline from raw data transformation and model training to activation, drive customer success through technical guidance, and contribute to extending product capabilities and shaping the AI product strategy. The role involves partnering with the product team to advance the platform's self-learning capabilities.

What you'd actually do

  1. Design RL use cases from the ground up
  2. Build and own the full ML pipeline
  3. Drive customer success
  4. Extend product capabilities
  5. Partner with the Braze Product team

Skills

Required

  • Python (Pandas)
  • TensorFlow
  • Keras
  • scikit-learn
  • CatBoost
  • XGBoost
  • SQL
  • machine learning pipelines
  • model deployment
  • well-structured, modular, documented code
  • Git
  • CI/CD
  • testing frameworks
  • type-hinting
  • code reviews
  • scalable, maintainable solutions

Nice to have

  • Airflow
  • Kubernetes
  • Terraform
  • GCP
  • data integration/ETL
  • pipeline optimization
  • reinforcement learning algorithms

What the JD emphasized

  • reinforcement learning algorithms

Other signals

  • Design RL use cases from the ground up
  • Build and own the full ML pipeline
  • Drive customer success
  • Extend product capabilities
  • Partner with the Braze Product team
  • Shape BrazeAI product strategy and roadmap