Forward-deployed Data Scientist

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

Braze is seeking a Forward-Deployed Data Scientist to partner with customers on AI implementations, including ML model configuration and data integration. The role involves extending product capabilities by developing data pipelines and APIs, and working with the RL pipeline development team to refine reinforcement learning algorithms. The position also contributes to BrazeAI product strategy and roadmap through customer insights.

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
  • customer-facing or consulting roles
  • working directly with clients and cross-functional teams
  • translating technical concepts into clear business value
  • identify opportunities and risks early
  • troubleshoot obstacles
  • drive creative solutions
  • stay current with industry trends
  • explore new tools/technologies
  • explain complex technical ideas persuasively

Nice to have

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

What the JD emphasized

  • reinforcement learning (self-learning) algorithms
  • reinforcement learning algorithms

Other signals

  • customer-facing AI product
  • ML model configuration
  • reinforcement learning algorithms
  • BrazeAI product strategy