Braze
Enterprise · Marketing automation
Enterprise · Marketing automation
Currently tracking 16 active AI roles, up 102% versus the prior 4 weeks. Primary focus: Post-train · Engineering. Salary range $98k–$165k (avg $138k).
| Title | Stage | AI score |
|---|---|---|
| Forward-Deployed Data Scientist II 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. | Post-trainData | 7 |
| Forward-Deployed Data Scientist II 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. |
| Post-trainData |
| 7 |
| Forward-Deployed Data Scientist II 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. | Post-trainData | 7 |
| Forward-Deployed Data Scientist II 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. | Post-trainData | 7 |