Senior Data Scientist

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

What We're Looking For

We're looking for a Senior Data Scientist to help build the intelligence layer behind ARQ's financial products. You'll work on some of our most important risk and financial crime challenges, developing machine learning models that help us detect fraud, prevent losses, and make better decisions at scale.

This is a highly impactful role where you'll take problems from idea to production — partnering with Product, Engineering, and Operations teams to turn large-scale datasets into models that directly influence customer and business outcomes.

You'll join a fast-growing team helping build the future of financial services for more than 2 million customers across the Americas.

What You'll Be Doing

• Design, build, and deploy machine learning models that solve real-world financial crime and risk challenges.




• Work on problems such as fraud detection, chargeback prediction, anomaly detection, identity verification, and transaction monitoring.




• Transform ambiguous business problems into measurable ML solutions.




• Partner closely with Product and Operations teams to define requirements, success metrics, and decision frameworks.




• Analyse large datasets to identify patterns, opportunities, and risks.




• Build and maintain production-ready data pipelines and model-serving solutions.




• Monitor model performance and continuously improve accuracy, reliability, and business impact.




• Collaborate with Data Engineering and Backend Engineering teams to operationalise machine learning at scale.




• Help shape the future of AI and machine learning capabilities across ARQ.

What You'll Need

• 5+ years of experience across Data Science, Machine Learning, Software Engineering, or related disciplines.




• Strong Python skills and experience working with large-scale datasets.




• Proven experience developing and deploying machine learning models in production environments.




• Strong understanding of supervised learning techniques, particularly classification problems.




• Experience with anomaly detection, fraud prevention, risk modeling, or related domains.




• Ability to translate business challenges into data-driven solutions.




• Experience working cross-functionally with Product, Engineering, and business stakeholders.




• Strong communication skills and a pragmatic approach to problem-solving.




• Comfortable operating in fast-moving environments with high ownership.

Nice To Have

• Experience in financial crime, fraud prevention, AML, risk, or payments.




• Experience in fintech, banking, or financial services.




• Backend engineering experience and familiarity with production systems.




• Experience building real-time decisioning or risk platforms.




• Familiarity with modern MLOps practices and model monitoring.

Benefits

• Competitive salary and benefits




• Stock options, so you own part of what you build




• Discretionary performance bonus




• The latest tools and technology




• A world-class team that will challenge and grow your skills




• The opportunity to help build the best fintech app in Latin America




• Office Policy: 3-4 days a week in-office