Staff Data Scientist - Fraud
Staff Data Scientist - Fraud
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Job Description
The Fraud team at Wise is dedicated to safeguarding our platform against financial crime and ensuring the protection of our legitimate customers. Leveraging cutting-edge machine learning real-time transaction monitoring and data analysis our team is responsible for developing and enhancing fraud detection systems. Software engineers data analysts and data scientists collaborate on a daily basis to continuously improve our systems and provide support to our fraud investigation team.
Our vision is:
Build a globally scalable fraud prevention and detection engine to maintain Wise as a secure environment for our legitimate customers.
Utilise machine learning techniques to identify potential risks associated with customer activity.
Foster a strong partnership between our fraud investigators and the product team to develop solutions that leverage the expertise of fraud prevention specialists.
Not only meet the requirements set by regulators and auditors but also surpass their expectations.
We are looking for a highly skilled Staff Data Scientist to lead technical innovation and drive the development of advanced data science solutions. This role is pivotal in enhancing our fraud detection capabilities and ensuring the security of our platform.
Heres how youll be contributing:
Innovate and Develop: Lead the development and deployment of machine learning models including neural networks anomaly detection graph-based models Transformers.
Lead and Collaborate: Mentor team members and promote adoption of AI workflows for automation across the business. Collaborate with cross-functional teams to integrate data science solutions into Fraud prevention product offerings.
Deploy and Integrate: Develop scalable deployment strategies together with Platform teams and integrate LLMs with AI agents for seamless production use.
Optimise and Evaluate: Conduct large-scale training and hyper-parameter tuning and define performance metrics to ensure high-quality model outputs.
Data Strategy and Management: Design and implement strategies for data collection curation and augmentation to support robust model training.
Documentation and Reporting: Communicate complex data findings to non-technical stakeholders effectively. Document the development and maintenance processes for models and features.
Qualifications :
Demonstrated expertise (5 years) in developing and deploying production-grade AI systems and Machine Learning (ML) in the fraud or risk domain.
Technical Proficiency: Skilled in Python capable of delivering production-ready Python services as required; possesses hands-on experience with neural networks and deep learning models; has comprehensive knowledge of machine learning frameworks such as TensorFlow or PyTorch as well as AI agent frameworks like LLamaIndex and LangGraph; well-versed in LLM orchestration and MCP usage.
Data-driven mindset: skilled in designing data strategies including data collection curation and augmentation to support model development. Experience with big-data frameworks and working with large scale databases
Technical leadership and mentorship: demonstrated ability to guide mentor and level-up teams on technical aspects fostering a collaborative and innovative work environment
Excellent communication skills capable of simplifying complex technical concepts for easy understanding; able to adapt communication style to suit different audiences; can effectively engage and advise both technical and non-technical stakeholders with clarity and logic
A strong product mindset with the ability to work independently in a cross-functional and cross-team environment;
Additional Information :
Were people without borders without judgement or prejudice too. We want to work with the best people no matter their background. So if youre passionate about learning new things and keen to join our mission youll fit right in.
Also qualifications arent that important to us. If youve got great experience and youre great at articulating your thinking wed like to hear from you.
And because we believe that diverse teams build better products wed especially love to hear from you if youre from an under-represented demographic.
For everyone everywhere. Were people building money without borders without judgement or prejudice too. We believe teams are strongest when they are diverse equitable and inclusive.
Were proud to have a truly international team and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what its like to work at Wise visit .
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
