Wise
Lead Data Scientist - Fraud Prevention
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Lead Data Scientist – Fraud Risk Team
About Wise
Wise is a global technology company, building the best way to move and manage the world’s money. Our mission: Min fees. Max ease. Full speed. We make it easier for individuals and businesses to send money internationally, spend abroad, and conduct international payments—while saving them money. We envision an entirely new network for the world's money, for everyone, everywhere.
About the Role
The Fraud team at Wise safeguards our platform against financial crime and protects our legitimate customers. Combining cutting-edge machine learning, real-time transaction monitoring, and data analysis, our team builds and enhances fraud detection systems. We foster collaboration between software engineers, data analysts, and data scientists to continuously improve our systems and support fraud investigations.
Our vision is to:
- Build a globally scalable fraud prevention and detection engine, maintaining a secure environment for Wise’s customers.
- Use machine learning to identify risks in customer activity.
- Strengthen partnerships between fraud investigators and the product team, leveraging specialist expertise.
- Exceed the expectations of regulators and auditors.
We’re seeking a highly motivated Lead Data Scientist to:
- Maintain, optimise, and refine existing ML models.
- Develop new fraud intelligence and reduce false positives impacting good customers.
- Support the Fraud Risk Team in managing and mitigating risks related to our receiving processes.
- Help grow our data science team within the fraud domain.
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Key Responsibilities
Model Maintenance & Improvement
- Maintain and optimise existing risk models for accuracy and reliability.
- Continuously monitor model performance, implementing improvements through feedback and testing.
- Manage advanced model deployment from data preprocessing to feature selection, evaluation, and monitoring.
Innovation & Development
- Lead the development and deployment of machine learning models and features.
- Install and update fraud detection intelligence in production.
Data Analysis & Intelligence Creation
- Conduct thorough data analysis to uncover trends, patterns, and anomalies that support risk mitigation.
- Develop actionable insights to guide the Fraud Risk Team's strategies.
Collaboration & Communication
- Work closely with the Fraud Risk Team and cross-functional teams to grasp business processes and identify risk factors.
- Communicate complex data findings clearly to non-technical stakeholders.
Risk Reduction Initiatives
- Identify data-driven strategies to reduce risk impact on good customers while balancing risk mitigation with satisfaction.
- Develop and test interventions to align with regulatory expectations.
Documentation & Reporting
- Document model development, maintenance, and processes.
- Create and present detailed reports and dashboards reflecting risk assessments and model performance.
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Qualifications
Essential
- Proven track record of developing ML models from scratch, including:
- Data preprocessing
- Feature engineering
- Model selection
- Evaluation
- Monitoring
- Strong Python knowledge (ability to review and co-develop with Java services).
- Hands-on experience with statistical analysis and the ability to articulate findings.
- Self-driven, product-oriented mindset with experience working independently in cross-functional environments.
- Strong communication skills—ability to translate technical insights clearly to non-experts.
- Exceptional problem-solving skills, particularly in refining problem definitions and solutions.
Nice-to-Have
- Expertise in unsupervised algorithms.
- Background in the fraud domain with a deep understanding of detection techniques.
Why Join Wise?
- A borderless team without prejudice—we hire based on passion, learning potential, and mission alignment.
- Diverse teams produce better outcomes—we actively seek applicants from under-represented backgrounds.
- Pride in global diversity and inclusion: We celebrate our international team and champion equity, respect, and career growth for all.
**Join us and shape the future of money—**for wiser choices, for everyone.
Salary Range: £90,500–£127,000 per year
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