Teams at Bureau (bureau.id)

Build and maintain graph-native fraud and identity-risk models using GNNs, embeddings, and graph algorithms. Support statistical, AI/ML, and deep-learning model design, training, evaluation, experimentation, data preparation, and production-adjacent pipeline work. Write production-quality Python and SQL-backed code, contribute to ML observability, and document solutions. The role suits candidates with 1–3 years of data science or ML engineering experience and strong fundamentals.

Analyze transaction and API performance data to identify product optimization opportunities, investigate verification failures, benchmark services, and report actionable insights. Own data sourcing and quality for OCR training sets, including document sourcing, volume management, and tagging. Use SQL and data visualization to recommend improvements to Engineering and Product teams.

Own the vision, strategy, and roadmap for Bureau’s RASP mobile security product across Android and iOS. Translate emerging mobile threats into effective protections, partner with engineering on SDK and platform delivery, improve onboarding and policy experiences, and connect RASP signals with identity and fraud products. Engage enterprise security and fraud leaders, support positioning and pricing, define product metrics, and scale the product from early release to adoption.