Senior Forward-Deployed Data Scientist

<div class="content-intro"><p>At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew.</p> <p>We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.</p> <p>To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.</p> <p>Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.</p> <p>If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you.</p></div><p><strong>WHAT YOU'LL DO</strong></p> <p>As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:</p> <ul> <li>Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration</li> <li>Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components</li> <li>Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms</li> <li>Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise</li> <li>Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success</li> </ul> <p><strong>WHO YOU ARE</strong></p> <ul> <li>Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred</li> <li>Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred</li> <li>Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment</li> <li>Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions</li> <li>Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms</li> <li>Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value</li> <li>Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions</li> <li>Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow</li> <li>Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences</li> </ul> <p>For candidates based in the United States, the pay range for this position at the start of e ... (truncated, view full listing at source)