Forward-Deployed Data Scientist

ABOUT THE ROLE We are seeking a highly skilled Forward-Deployed Data Scientist to join our AI Deployment team at Braze. As a key member of our team, you will design and build end-to-end machine learning solutions that power 1-to-1 personalization for some of the world's leading brands. Our ideal candidate is a creative technical expert with a passion for solving complex challenges and a bias towards action in the face of change. WHAT YOU'LL DO As a Forward-Deployed Data Scientist, you will be responsible for designing and building machine learning solutions that optimize for real business value. Your key responsibilities will include: - Designing reinforcement learning use cases from the ground up, taking into account the complexity of modern marketing journeys and proactively identifying risks to set each engagement up for success - Building and owning the full ML pipeline, taking customers' raw data through transformation, model training, and activation to deliver model decisions that personalize experiences for millions of end users - Driving customer success by providing ongoing technical guidance that ensures data science performance, successful adoption, and measurable outcomes - Extending product capabilities by developing features and tools that support the broader AI deployment team and scale what's possible across engagements - Partnering with the Braze Product team to refine and advance Braze's reinforcement learning algorithms, pushing the self-learning capabilities of the platform forward - Shaping BrazeAI product strategy and roadmap by bringing customer-facing insights and deep technical expertise to the table WHAT YOU'LL NEED To be successful in this role, you will need: - A Bachelor's degree in Computer Science, Data Science, Mathematics, Engineering, or a related field - 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 - Strong technical expertise in Python (Pandas), core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost), and SQL for querying/manipulating datasets - Experience in machine learning pipelines and model deployment - Engineering best practices, including writing well-structured, modular, documented code and following strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews) - Nice-to-have skills in DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms - Excellent communication and problem-solving skills, with the ability to work directly with clients and cross-functional teams WHY REMOTE As a remote worker, you will have the flexibility to work from anywhere and enjoy a better work-life balance. Braze offers a range of benefits to support your remote work experience, including flexible paid time off, comprehensive benefit plans, and professional development opportunities. BENEFITS Braze offers a competitive compensation package that may include equity, as well as a range of benefits, including: - Competitive compensation - Retirement and Employee Stock Purchase Plans - Flexible paid time off - Comprehensive benefit plans covering medical, dental, vision, life, and disability - Family services, including fertility benefits and equal paid parental leave - Professional development, including formal career