Position Details
About this role
Senior data scientist focusing on forward-deployed ML for BrazeAI, collaborating with customer teams to define use cases, build data pipelines, and deploy reinforcement-learning based solutions in production.
Key Responsibilities
- Collaborate with customer Analytics/BI teams on use case definition, data integration, pipeline setup, and ML model configuration
- Extend product capabilities by building reusable data pipelines, APIs, and components
- Refine reinforcement learning algorithms with the RL pipeline team
- Provide technical expertise to ensure successful adoption and measurable customer outcomes
- Shape BrazeAI product strategy and roadmap with customer-facing insights
Technical Overview
Stack includes Python, Pandas, TensorFlow/Keras/scikit-learn/CatBoost/XGBoost, SQL, BigQuery-like data handling, with production-grade pipelines deployed on Kubernetes with Airflow, Terraform, in Google Cloud Platform.
Ideal Candidate
The ideal candidate is a senior data scientist with 3+ years of hands-on experience deploying ML in production, strong Python and ML library skills, and experience building data pipelines for customer-facing deployments. They excel at cross-functional collaboration, communicate complex concepts clearly, and can translate business needs into scalable ML solutions.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Bachelor's degree required, 3-5+ years of hands-on data science/ML production experience, onsite in Toronto
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