About the job
At Braze, we pride ourselves on nurturing a culture that is approachable, kind, and passionately engaged. We are committed to fostering an environment where high standards are the norm, teamwork is championed, and work-life harmony is prioritized as we navigate our rapid global growth while advocating for equity and opportunities both within and outside our organization.
To thrive in this environment, you must be ready to hold yourself and those around you to high standards. Every team member has the opportunity to contribute meaningfully: embracing autonomy, taking accountability, and being open to new ideas are crucial to our collective success.
Our insatiable curiosity for learning and desire to share our diverse passions create a unique vibrancy within our culture.
If you are motivated to tackle exhilarating challenges and possess a proactive mindset in the face of change, you will be empowered to make a significant impact here, supported by a sharp and enthusiastic team. If Braze resonates with your aspirations, we eagerly anticipate meeting you.
WHAT YOU'LL DO
As we expand our customer base driven by the excitement surrounding BrazeAI, we are looking to grow our team! Join our group of Forward-Deployed Data Scientists, who are creative technical experts partnering with customers to ensure their success. In this role, you will:
- Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration.
- Enhance product capabilities by refining architecture and developing reusable data pipelines, APIs, and components.
- Work closely with the RL pipeline development team to improve and advance our reinforcement learning algorithms.
- Contribute to shaping BrazeAI product strategy and roadmap through valuable customer-facing insights and technical expertise.
- Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success.
WHO YOU ARE
- Education: A Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field is required; a Master’s or PhD in a relevant technical discipline is preferred.
- Experience: 3-5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or in a similar role dealing with large-scale data and production environments. Experience in customer-facing or consulting roles is highly preferred.
- Technical Skills: Proficient in Python (Pandas) and core ML libraries including TensorFlow, Keras, scikit-learn, and CatBoost.