Overview
As a Forward-Deployed Data Scientist at Braze, you design and implement end-to-end ML solutions for 1-to-1 personalization on major brands. You own the data-to-model-to-activation pipeline and guide clients to measurable outcomes. You collaborate with product and customers to extend capabilities and advance AI features, shaping BrazeAI and our platform’s self-learning potential. You work in a fast-growing, collaborative environment that values autonomy and learning.
Pay / Benefits
- Competitive compensation
- Equity plan / ESPP
- Flexible paid time off
- Comprehensive health plans (medical, dental, vision)
- Family benefits including fertility support and parental leave
- Professional development stipend
Responsibilities
- Design ML use cases from the ground up, aligning scope with business value and marketing journey complexity
- Build and own the full ML pipeline from raw data to activation for large-scale personalization
- Provide ongoing technical guidance to ensure data science performance and adoption
- Develop features and tools to extend the AI deployment capabilities and scale engagements
- Partner with Product to advance reinforcement learning algorithms and self-learning capabilities
- Contribute to BrazeAI product strategy and roadmap with customer-facing insights and technical expertise
Key requirements
- Bachelor in Computer Science, Data Science, Mathematics, Engineering, or related field; Master’s or PhD preferred
- 3–5+ years of hands-on Data Scientist or ML Engineer experience in large-scale data and production environments
- Proficiency in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost)
- Strong SQL skills and experience with ML pipelines and model deployment
- Solid software engineering practices (Git, CI/CD, testing, type hints, code reviews) and ability to build scalable, maintainable solutions
- Customer-facing or consulting experience is strongly preferred
- Customer collaborator
- Entrepreneurial problem-solver
- Continuous learner
- Python (Pandas)
- TensorFlow, Keras, scikit-learn, CatBoost, XGBoost
- SQL
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