W

Wise

Low-cost international money transfers with API

Lead Data Scientist - Anti-Money Laundering

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeLondon, UK£90.5k - £127k /yrHybrid

About the Job

Requirements

  • Experience implementing, training, testing, and evaluating the performance of machine learning systems.
  • Strong knowledge of Python; familiarity and experience with object-oriented programming principles are a plus.
  • Experience with statistical analysis and the ability to produce well-designed experiments.
  • A strong product mindset and the ability to work independently in a cross-functional and cross-team environment.
  • Good communication skills and the ability to explain ideas to non-technical people.
  • Strong problem-solving skills and the ability to refine problem statements and determine how to solve them.

Responsibilities

  • Develop efficient and effective anti-money-laundering detection controls using unsupervised, semi-supervised, and supervised learning with generative artificial intelligence.
  • Create frameworks to prove control coverage at a regional level.
  • Develop technologies to serve Wise’s diverse international user base.
  • Work across functions to own and solve anti-money-laundering-related problems globally.
  • Mentor junior team members on technical and non-technical skills.
  • Evaluate anti-money-laundering systems against internal and external benchmarks.
  • Develop decisioning layers to identify optimal trade-offs between precision and recall.
  • Provide data-driven insights on potential outcomes under various scenarios.
  • Collaborate with operational teams to refine processes and ensure effective feedback integration into automation systems.
  • Design and manage projects that use excess operational capacity, such as manual data labeling to improve models.
  • Create systems that provide investigators with in-depth insights into red flags and typologies on profiles and transactions.
  • Package algorithms into deployable libraries or objects and transition them from staging to production environments.
  • Implement and maintain scheduled data-gathering and model-retraining processes using automated pipelines.
  • Maintain production-grade Python services.

Desired Qualifications

  • Familiarity with automating operational processes through technical solutions, such as large language models.
  • Willingness to work alongside operational teams to understand their pain points.
  • Knowledge and experience in the financial crime domain.

About the Company

Wise

Low-cost international money transfers with API

Wise enables international money transfers with lower fees by using a peer-to-peer model to match transfers across borders. It offers a multi-currency account for holding and managing money in different currencies and provides an API for businesses to integrate Wise transfers into their platforms. Unlike traditional banks that charge higher fees and poor exchange rates, Wise uses transparent, small-per-transaction fees and real-time exchange rates to reduce costs. Its approach differentiates it from competitors by emphasizing simplicity, cost transparency, and a broad API for business integration. The goal is to make cross-border payments cheaper, faster, and more transparent for individuals and businesses around the world.

Company size
10,001+
Company stage
IPO
Headquarters
London, United Kingdom
Founded
2011

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