Lead Data Scientist — KYC & Onboarding (Hybrid)

Wise

Greater London

Hybrid

GBP 91,000 - 127,000

Full time

14 days+

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Benefits offered by this job

Flexible working
Stock options
Relocation support
Generous parental leave
Pension scheme
Paid sabbatical
Development opportunities
Sports and wellbeing compensation
Social activities and events

Job summary

Wise in London is hiring a Technical Lead Data Scientist (IC3) to join the KYC Global and Onboarding Team. You’ll own training, evaluation and management of ML models for document verification, shaping scalable data pipelines and improving customer onboarding experiences.

You’ll mentor junior team members, collaborate with cross-functional partners, and keep up-to-date with ML research to apply practical, production-ready solutions that help millions of customers move money securely.

Qualifications

  • Experience in building and deploying ML models for onboarding or risk.
  • Ability to design and iterate ML solutions end-to-end.
  • Strong Python coding and data processing skills.

Responsibilities

  • Own training, iteration and management of ML models life cycle for KYC.
  • Develop and maintain large Python codebase with best practices.
  • Collaborate with cross-functional teams to deploy production ML systems.
  • Mentor junior data scientists and promote data science standards.
  • Research KYC verification domain to prevent fraud.

Skills

Machine learning
Python
Deep learning
KYC domain knowledge
Model evaluation

Tools

PyTorch
TensorFlow
Pandas
Scikit-learn

Job description

Wise in London is hiring a Technical Lead Data Scientist (IC3) to join the KYC Global and Onboarding Team. You’ll own training, evaluation and management of ML models for document verification, shaping scalable data pipelines and improving customer onboarding experiences.

You’ll mentor junior team members, collaborate with cross-functional partners, and keep up-to-date with ML research to apply practical, production-ready solutions that help millions of customers move money securely.

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