Senior Machine Learning Engineer II - FinCrime

Wise
London
Workplace: OnsiteFull timeGBP 111,000 - 145,000 annuallyFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Cross-functional collaboration","Autonomous execution"]

Own the integrity of Risk ML labels by building and operating the label-side quality and monitoring layer. Define statistical fundamentals and quality metrics, design automated audit processes over time, and help run the end-to-end ML lifecycle from training and evaluation to deployment. Work with cross-functional partners across Risk Intelligence, Data Engineering, and Product to ensure ML learns from clean, reliable data.

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FursaFursa
Wise
Wise
4 days ago

Senior Machine Learning Engineer II - FinCrime

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Source: Company careers pageValidated by: Fursa AI
Last checked: 14 hours agoStatus: Live

Job Summary

Own the integrity of Risk ML labels by building and operating the label-side quality and monitoring layer. Define statistical fundamentals and quality metrics, design automated audit processes over time, and help run the end-to-end ML lifecycle from training and evaluation to deployment. Work with cross-functional partners across Risk Intelligence, Data Engineering, and Product to ensure ML learns from clean, reliable data.
Location: London
Workplace: Onsite
Employment Type: Full time · Permanent
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build, scale, and maintain the integrity layer of 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 across machine learning model training, evaluation, and pipeline deployment.
  • •Collaborate with cross-functional partners across Risk Intelligence, Data Engineering, and Product.

Pay and Benefits

Salary: GBP 111,000 - 145,000 annually
Equity and Bonus:Equity

Key Requirements

  • •A degree in STEM (Computer Science, Mathematics, Statistics, Physics, Chemistry, Electrical Engineering, or a related quantitative field).
  • •Strong mathematical and statistical fundamentals with proven application of statistical analysis to complex data environments.
  • •Hands-on experience across model training, evaluation, and deployment using ML/AI/Neural Networks or NLP frameworks.
  • •Strong proficiency in Python or Java for data scripting and production engineering, plus advanced SQL capability.
  • •Experience building static data pipelines and doing deep-dive data analysis with data visualization tools to understand statistical behavior.
Experience:FintechE-commerce
Education:Bachelor's in STEM (Computer Science, Mathematics, Statistics, Physics, Chemistry, Electrical Engineering, or related quantitative field)
Skills:Cross-functional collaborationAutonomous execution
Languages:English
Tech Stack:PythonJavaSQLKafkaGraph Neural NetworksSVMNLPTransformersLSTMs

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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