Data Scientist (Fraud & Risk)

Location: Cambridge, United Kingdom. Hybrid role requiring office attendance three set days per week, Tuesday–Thursday, with office presence expected 50% or more of the time based on business needs.

Company

hirify.global develops payments technology, while Featurespace builds fraud and financial crime prevention technology for financial institutions.

What you will do

• Develop machine-learning models using complex transactional datasets.
• Work with customers, product managers, engineers, and delivery teams to turn real-world problems into fraud and risk prevention products.
• Take models from discovery and experimentation through production deployment.
• Monitor deployed models, investigate performance changes, and identify improvements.
• Retrain, enhance, and safely release models as data, customer needs, and fraud patterns evolve.
• Measure and communicate product impact, contribute to model governance and documentation, share knowledge, mentor colleagues, and improve team processes.

Requirements

• Experience implementing machine-learning models or analytical algorithms in software.
• Experience using Python, Java, or another major programming language for data analysis or machine learning.
• Experience using SQL to analyse data.
• Practical experience working with large, diverse datasets.
• Strong analytical and problem-solving skills, particularly for data-centric problems.
• Ability to learn new technologies and concepts quickly.
• Experience collaborating with multiple stakeholders on technical projects.
• Clear and concise written and verbal communication, with the ability to manage and prioritise own work.
• Degree in a scientific or numerate discipline, or equivalent professional experience.

Culture & Benefits

• Collaborative Cambridge-based Data Science group focused on fraud and risk.
• Opportunities for informal learning, mentoring, and exchanging ideas with experienced colleagues.
• Hybrid work arrangement combining remote work with regular office attendance.