Braze

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.

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.

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.

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.

Data Scientist, AI Deployment at Braze, responsible for designing and building end-to-end ML solutions for customer personalization. This role involves owning the full ML pipeline from data transformation and model training to activation, and extending product capabilities. They will also partner with the Product team to advance reinforcement learning algorithms and shape AI product strategy.

This role focuses on designing and building end-to-end machine learning solutions, specifically RL use cases, for customer engagement personalization. The individual will own the full ML pipeline from data transformation to model training and activation, drive customer success through technical guidance, and contribute to extending product capabilities and shaping AI product strategy. The role involves partnering with the product team to advance reinforcement learning algorithms and bring customer-facing insights to the product roadmap.

This role focuses on designing and building end-to-end machine learning solutions, specifically RL use cases, for customer engagement personalization. The individual will own the full ML pipeline from data transformation to model training and activation, drive customer success through technical guidance, and contribute to extending product capabilities and shaping AI product strategy. The role involves partnering with the product team to advance reinforcement learning algorithms and bring customer-facing insights to the product roadmap.

The Forward-Deployed Data Scientist II at Braze partners with customers to ensure their success with BrazeAI. This role involves collaborating on implementations, extending product capabilities by improving architecture and developing data pipelines, refining reinforcement learning algorithms, contributing to product strategy, and providing technical expertise for customer adoption and success. The role requires strong Python, ML libraries, SQL, and ML pipeline/deployment experience, with a preference for customer-facing roles and experience with RL algorithms.

The Data Scientist, AI Deployment role at Braze focuses on designing and building end-to-end machine learning solutions for customer personalization. This involves managing the full ML pipeline from data transformation and model training to activation, with a strong emphasis on customer success and extending product capabilities. The role also involves shaping the AI product strategy and roadmap, particularly concerning reinforcement learning algorithms.

The AI Platform Engineer II will build and scale BrazeAI Decisioning Studio, a reinforcement learning platform for personalized customer engagement. This role involves working with cloud-native infrastructure, data-intensive systems, and production machine learning, focusing on building and maintaining critical services, implementing scalable cloud solutions, troubleshooting production issues, and collaborating with data scientists and ML engineers.

Senior Software Engineer to design, improve, and scale Braze's self-learning (reinforcement learning) AI platform for marketing personalization. The role involves building modular components for Decisioning Studio, working with cross-functional teams, and influencing product strategy.

Senior Forward Deployed Data Scientist, AI Deployment role at Braze, focusing on customer-facing AI implementations. This role involves collaborating with customers and internal teams on ML model configuration, data pipelines, and improving architecture. It also includes working with the RL pipeline development team and contributing to product strategy. The goal is to ensure successful adoption and measurable outcomes for customers using Braze's AI capabilities.

The Forward Deployed Data Scientist, AI Deployment role at Braze focuses on partnering with customers to implement and ensure success with BrazeAI. This involves defining use cases, integrating data, setting up pipelines, configuring ML models, and improving architecture. The role also involves refining reinforcement learning algorithms, contributing to product strategy through customer insights, and providing ongoing technical expertise for customer adoption and success. The position requires strong Python, ML libraries, SQL, and ML pipeline experience, along with engineering best practices.

The Forward-Deployed Data Scientist at Braze partners with customers to implement BrazeAI solutions, focusing on ML model configuration, data integration, and refining reinforcement learning algorithms. This role extends product capabilities by developing reusable data pipelines and components, and contributes to product strategy through customer insights.

Senior Data Scientist role focused on deploying and refining AI models, particularly reinforcement learning algorithms, for customer engagement within the Braze platform. This involves collaborating with customers and internal teams on implementation, pipeline setup, and contributing to product strategy.

Senior Data Scientist role focused on deploying and refining AI models, particularly reinforcement learning algorithms, for customer engagement within the Braze platform. This involves collaborating with customers and internal teams on implementation, pipeline setup, and contributing to product strategy.