Senior Data Scientist - Fraud & Risk ML, Relocation to Abu Dhabi

UMATR; Abu Dhabi; On-site; AED 391,000 - 446,000; Full time

Benefits offered by this job

Relocation flights

Temporary accommodation provided

Job summary

UMATR is seeking a Senior Data Scientist in Abu Dhabi to build and improve machine-learning models that identify suspicious activity and emerging risks across large-scale digital interactions. The role combines research-led modelling with production readiness in a high-stakes environment.

You will apply statistical modelling, supervised learning and neural networks to detect rare events, ensure explainability and scale models for real-time decisions. Relocation support is provided.

Qualifications

• 5+ years of experience in data science or machine learning, with a strong focus on modelling.
• Experience building models for fraud, risk, security or other rare-event problems.
• Strong knowledge of classification, predictive modelling and structured data.
• Experience working with rare events and highly imbalanced datasets.
• Excellent statistical reasoning, experimental-design and feature-engineering skills.
• Expert-level Python and strong software-engineering fundamentals.
• Experience taking models from research and experimentation through validation and production.
• Understanding of model explainability, monitoring and drift detection.
• Experience with large-scale behavioural, transactional, operational or event-based datasets.
• Experience working with dynamic, high-volume datasets is advantageous.

Responsibilities

• Detect rare risk events across millions of legitimate interactions while controlling false positives.
• Identify new and evolving patterns before large labelled datasets are available.
• Build models for risk scoring, fraud prevention and anomaly detection.
• Distinguish legitimate changes in activity patterns from anomalous events.
• Engineer signals from large-scale event, interaction and transactional data.
• Monitor model performance and respond to changing patterns and data drift.
• Develop explainable models that help stakeholders understand why activity has been flagged.
• Improve the reliability and scalability of models used in real-world decision systems.

Skills

Python

ML modelling

Statistical reasoning

Feature engineering

Model explainability

Production deployment

Job description

UMATR is seeking a Senior Data Scientist in Abu Dhabi to build and improve machine-learning models that identify suspicious activity and emerging risks across large-scale digital interactions. The role combines research-led modelling with production readiness in a high-stakes environment.

You will apply statistical modelling, supervised learning and neural networks to detect rare events, ensure explainability and scale models for real-time decisions. Relocation support is provided.