Senior Data Scientist — Fraud & Risk ML (Hybrid)

Castleisland; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Stock options

Discretionary bonus

Latest tools & tech

World-class team

In-office 3-4 days a week

Job summary

Castleisland is seeking a Senior Data Scientist to build the intelligence layer behind ARQ's financial products. You will develop ML models to detect fraud, prevent losses, and scale decisions across millions of customers.

In this role you will take problems from idea to production, partnering with Product, Engineering, and Operations to turn large datasets into measurable impact. The position is hybrid, with in-office collaboration.

Qualifications

• 5+ years of experience across Data Science, ML, or related disciplines.
• Strong Python skills and large-scale data handling.
• Proven production ML model deployment experience.

Responsibilities

• Design, build, and deploy ML models that solve financial crime and risk challenges.
• Work on fraud detection, anomaly detection, identity verification, and transaction monitoring.
• Transform business problems into measurable ML solutions.
• Partner with Product and Operations to define requirements and metrics.
• Analyze large datasets to identify patterns and risks.
• Build and maintain production data pipelines and model-serving solutions.
• Monitor performance and improve accuracy and impact.
• Collaborate with Data and Backend Engineering to operationalise ML at scale.
• Help shape the future of AI and ML capabilities across ARQ.

Skills

Python

ML models

Production ML

Large-scale data

Cross-functional collab

Tools

MLOps

Job description

Castleisland is seeking a Senior Data Scientist to build the intelligence layer behind ARQ's financial products. You will develop ML models to detect fraud, prevent losses, and scale decisions across millions of customers.

In this role you will take problems from idea to production, partnering with Product, Engineering, and Operations to turn large datasets into measurable impact. The position is hybrid, with in-office collaboration.