Staff Data Scientist - AML at Wise

on-site · full-time · Visa sponsorship

Apply for this role at Wise

Responsibilities:
- Lead research and development of production ML models for AML: anomaly detection, graph models, neural networks and Transformer-based systems.
- Design modular, evidenceable detection pipelines that surface typologies and red flags across regions.
- Collaborate with AML investigators, product and platform teams to embed models into real-time monitoring and investigation workflows.
- Define evaluation metrics, validation strategies and explainability to meet regulatory and audit requirements.
- Build scalable deployment and monitoring patterns with platform engineers; own model lifecycle (training, testing, serving, monitoring).
- Mentor data scientists and promote best practices in modelling, reproducibility and data hygiene.

Requirements:
- 5+ years building production-grade ML systems, preferably in AML, fraud, risk or financial crime domains.
- Strong Python skills and deep learning experience with frameworks such as TensorFlow or PyTorch.
- Practical experience with graph-based models, anomaly detection methods and Transformer architectures.
- Familiarity with LLM orchestration and tools (LLamaIndex, LangGraph) is desirable for automation/augmentation tasks.
- Experience deploying models at scale, monitoring model performance and addressing concept drift.
- Excellent communication skills and ability to work with investigators, engineers and product managers to deliver practical solutions.
- Strong quantitative mindset, reproducible workflows and knowledge of big-data tooling/environments.