Forward-Deployed Data Scientist II
Braze is seeking a Forward-Deployed Data Scientist II to join our AI Deployment team, a group of creative technical experts dedicated to designing and building end-to-end machine learning solutions that power personalized experiences for leading global brands. This role offers the opportunity to work within a dynamic environment, contributing to the advancement of Braze's customer engagement platform.
In this position, you will be responsible for designing reinforcement learning use cases from the ground up, scoping solutions that optimize for real business value while accounting for the complexities of modern marketing journeys. You will build and own the full machine learning pipeline, transforming raw customer data through model training and activation to deliver personalized experiences to millions of end users. Additionally, you will provide ongoing technical guidance to ensure data science performance, successful adoption, and measurable outcomes. Your role will also involve developing features and tools to support the broader AI deployment team and collaborating with the Braze Product team to refine and advance our reinforcement learning algorithms.
The ideal candidate will possess a Bachelor's degree in Computer Science, Data Science, Mathematics, Engineering, or a related field, with a Master's or PhD preferred. You should have 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. Proficiency in Python (Pandas) and core machine learning libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost), as well as strong SQL skills for querying and manipulating datasets, are essential. Experience with machine learning pipelines, model deployment, and engineering best practices such as Git, CI/CD, testing frameworks, type-hinting, and code reviews is required. Additional experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, pipeline optimization, or reinforcement learning algorithms is advantageous. Strong communication skills and the ability to work directly with clients and cross-functional teams are also important.
Braze offers competitive compensation that may include equity, retirement and employee stock purchase plans, flexible paid time off, and comprehensive benefit plans covering medical, dental, vision, life, and disability. Family services include fertility benefits and equal paid parental leave. Professional development is supported through formal career pathing, learning platforms, and a yearly learning stipend. The company fosters a collaborative, transparent, and fun culture recognized as a Great Place to Work®.
Joining Braze means becoming part of a genuinely approachable, exceptionally kind, and intensely passionate team. The company values high standards, teamwork, and work-life harmony, striving for greater equity and opportunity both inside and outside the organization. If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, Braze offers an environment where you can thrive and make a real impact.