ML Engineer - Statistical Integrity (Financial Crime)

Wise
London
Workplace: OnsiteFull timeGBP 87,500 - 111,000 annuallyFunction: Data Science & Machine LearningEducation: bachelorsSkills: []

Build and scale the integrity layer for Risk ML label platforms, ensuring labels and statistical fundamentals are accurate and reliable for models that detect financial crime. Define, implement, and monitor quality metrics, and design automated audit processes to track label integrity over time. Work end-to-end across model training, evaluation, and deployment while collaborating with Risk Intelligence, Data Engineering, and Product partners.

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FursaFursa
Wise
Wise
23 hours ago

ML Engineer - Statistical Integrity (Financial Crime)

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Build and scale the integrity layer for Risk ML label platforms, ensuring labels and statistical fundamentals are accurate and reliable for models that detect financial crime. Define, implement, and monitor quality metrics, and design automated audit processes to track label integrity over time. Work end-to-end across model training, evaluation, and deployment while collaborating with Risk Intelligence, Data Engineering, and Product partners.
Location: London
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build, scale, and maintain the integrity layer for the label platform for Risk ML models.
  • •Define, implement, and monitor statistical fundamentals and key quality metrics for data and labels.
  • •Design automated audit processes to evaluate and monitor label quality over time.
  • •Work end-to-end on ML model training, evaluation, and pipeline deployment.
  • •Collaborate with cross-functional partners across Risk Intelligence, Data Engineering, and Product.

Pay and Benefits

Salary: GBP 87,500 - 111,000 annually
Equity and Bonus:Equity

Key Requirements

  • •Degree in a STEM field such as Computer Science, Mathematics, Statistics, Physics, Chemistry, or Electrical Engineering.
  • •Strong mathematical and statistical fundamentals with a proven track record applying statistical analysis to complex data environments.
  • •Hands-on ML lifecycle experience across training, evaluation, and deployment (frameworks around ML/AI/Neural Networks or NLP).
  • •Strong proficiency in Python or Java for scripting and production engineering, plus advanced SQL capability.
  • •Solid experience building static data pipelines, performing deep-dive data analysis, and using data visualization tools to understand statistical behavior.
Experience:Financial servicesFintech
Education:Bachelor's in STEM (Computer Science, Mathematics, Statistics, Physics, Chemistry, Electrical Engineering, or related quantitative field)
Languages:English
Tech Stack:PythonJavaSQLMachine LearningAINeural NetworksNLPTransformersLSTMsKafkaGraph Neural NetworksSupport Vector Machines

Company Brief

Wise
Wise (formerly TransferWise) is a London-based fintech that provides low-cost international money transfers, multi-currency accounts and payment infrastructure for individuals and businesses worldwide.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: London, United Kingdom
Founded: 2011
Glassdoor
Glassdoor: 3.8
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