Lead Data Scientist - Fraud Prevention

• Compensation: GBP 85,000 - GBP 115,000 - yearly

Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.

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 someone who will help maintain our existing machine learning algorithms, while helping to make them better and develop new intelligence to stop fraudsters.

Here’s how you’ll be contributing:

We are seeking a highly motivated Lead Data Scientist to join our Fraud Risk Team. In this role, you will level up the intelligence and maintain and refine existing models, develop new features, and create new intelligence to reduce the impact on good customers. You will work closely with the Fraud Risk Team to support the effective management and mitigation of risks associated with our receiving processes.

Further you will help grow our data science team in space.

• Model Maintenance and Improvement:
  Maintain and optimize existing risk models to ensure their accuracy and reliability.
• Continuously monitor model performance and implement improvements based on feedback and testing.
• Innovate and Develop:
  Lead the development and deployment of machine learning models, features and help deploy intelligence to production.
• Data Analysis & Intelligence Creation:
  Conduct thorough data analysis to identify trends, patterns, and anomalies that can aid in risk mitigation.
• Develop actionable intelligence and insights to inform the Fraud Risk Team's strategies.
• Collaboration & Communication:
  Work closely with the Fraud Risk Team to understand business processes and risk factors.
• Communicate complex data findings and insights effectively to non-technical stakeholders.
• Risk Reduction Initiatives:
  Identify opportunities to reduce the impact of risks on good customers through data-driven strategies and interventions.
• Develop and test strategies to balance risk mitigation with customer satisfaction.
• Documentation & Reporting:
  Document the development and maintenance processes for models and features.
• Prepare and present detailed reports and dashboards that reflect risk assessment outcomes and model performance.

• Proven track record of deploying models from scratch, including data preprocessing, feature engineering, model selection, evaluation, and monitoring;
• Solid knowledge of Python, and ability to make and justify design decisions in your code. You know how to use Git to collaborate with others (e.g. opening Pull Requests on Git Hub) and are able to review code. Ability to read through code, especially Java. Demonstrable experience collaborating with engineering on services;
• Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL);
• Experience with statistical analysis and good presentation skills to drive insight into action;
• A strong product mindset with the…