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Bureau is a unified risk decisioning platform for compliance, fraud, and transaction risk detection, serving over 150 banks, fintechs, retailers, and digital platforms globally. The platform is powered by a 1 billion+ identity knowledge graph and has raised $50M+ from top-tier investors including Sorenson Capital and PayPal Ventures.
In this Senior Data Scientist role, you will build and extend graph-native models (GNNs, embeddings, and custom graph algorithms) to detect fraud, collusion, and identity risk across banking and e-commerce networks. You'll design and deploy statistical, AI/ML, and deep learning models for fraud and risk detection, including real-time serving architectures. The role involves running experiments and light data pipeline work to fine-tune model performance, and shipping production-grade software backed by rigorous statistics and ML with built-in observability.
Bureau values self-motivated people who move fast, build systems from scratch, and care deeply about turning strategy into execution. The culture emphasizes performance over hours worked, with speed, ownership, and impact as core metrics. You'll work autonomously to find business impact in a scaling global company.
REQUIREMENTS:
- BS/MS/PhD in ML, CS, Math, Stats, or related field
- 4 to 7 years of experience in Data Science, AI/ML Engineering, or related roles
- Strong Python programming skills
- Cloud platform experience (AWS, Databricks, or Azure)
- SQL and DBT proficiency
- Experience with Athena or BigQuery
- Track record of shipping production ML systems, ideally in fintech fraud, risk, payments, or compliance domains
- Comfort with ambiguity, unlabeled data, and autonomous problem-solving
- Prior graph-modeling experience is a plus
