Senior Data Scientist, Fraud

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Model Development: Design, assess, and assist in the production of machine learning models aimed at fraud detection; take ownership of their continuous monitoring and retraining processes.

• Experimentation: Create and conduct experiments to evaluate the effectiveness of fraud interventions, striking a balance between customer experience and loss reduction.

• Risk Assessment: Analyze fraud typologies within our product lines to guide prioritization and investment strategies.

• System Maintenance: Develop and sustain anomaly detection systems to identify new fraud vectors before they expand.

• Cross-Functional Collaboration: Collaborate closely with fraud operations, engineers, product managers, and data analysts to convert model outputs into practical mitigations.

⛳️ Requirements

• A solid grounding in statistics, with a degree in a quantitative discipline (Statistics, Mathematics, Engineering, Computer Science, or similar).

• Over 5 years of experience in data science, decision science, or risk analytics related to fraud, payments, or financial crime.

• Practical experience in building and deploying machine learning models in a production setting; experience in fraud, risk, or financial services is a significant advantage.

• Strong foundation in data science principles: experimentation, statistical inference, model evaluation, and feature engineering.

• Proficiency in Python and SQL; comfortable engaging across the entire model development lifecycle.

• An inquisitive nature, with a passion for exploring data to uncover patterns that others may overlook.

• Ability to articulate technical insights clearly to non-technical stakeholders and convert findings into actionable strategies.

• Comfort in fast-paced, cross-functional teams with high expectations for ownership.

🏝️ Benefits

• Culture: We prioritize our people and focus on the well-being of every team member. Our company fosters an environment where all opinions are valued, and every voice matters. We respect each other and continuously support one another, emphasizing our humanity above all.

• Learning: We promote a learning and development-oriented culture, emphasizing knowledge sharing, training, and regular internal technical discussions.

• Compensation: Enjoy a competitive salary, pension, health insurance, monthly bonuses, along with additional benefits.