Forward-deployed Data Scientist II

Braze Braze · Enterprise · New York, NY · Customer Experience

The Forward-Deployed Data Scientist II at Braze partners with customers to ensure their success with BrazeAI. This role involves collaborating on implementations, improving architecture, developing data pipelines and components, refining reinforcement learning algorithms, and contributing to product strategy. The position requires strong Python and ML library proficiency, SQL skills, and experience with ML pipelines and model deployment, along with engineering best practices.

What you'd actually do

  1. Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
  2. Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
  3. Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
  4. Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
  5. Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

Skills

Required

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

Nice to have

  • DevOps tools (Airflow, Kubernetes, Terraform, GCP)
  • data integration/ETL
  • pipeline optimization
  • reinforcement learning algorithms
  • customer-facing or consulting roles
  • Master’s or PhD in a relevant technical discipline

What the JD emphasized

  • customer-facing
  • reinforcement learning (self-learning) algorithms
  • ML model configuration
  • data integration
  • pipeline setup

Other signals

  • customer-facing AI product
  • reinforcement learning algorithms
  • ML model configuration
  • data pipelines