Fraud Detection ML Engineer

Tanqeeb; Dubai; On-site; AED 180,000 - 240,000; Full time

Job summary

Tanqeeb in Dubai is seeking a Fraud Detection ML Engineer to design and deploy machine-learning models that identify fraudulent transactions and suspicious financial activity.

You will collaborate with data engineers to process high-volume transaction data, build real-time scoring systems, and monitor model performance to minimize false positives. A strong background in Python, ML libraries, and fraud/AML domains is expected.

Qualifications

• 4-8 years of experience in ML or fraud-detection roles.
• Strong Python and ML library proficiency (Pandas, Scikit-learn).
• Experience with real-time analytics and fraud/AML domain is a plus.

Responsibilities

• Develop fraud detection and anomaly detection models.
• Analyze transaction and customer behaviour.
• Build real-time fraud scoring systems.
• Collaborate with data engineering to process high-volume data.
• Monitor model performance and false positives.

Skills

Python

Machine Learning

SQL

Pandas

Scikit-learn

Real-time analytics

Fraud/AML experience

Tools

PySpark

Kafka

Job description

Fraud Detection ML Engineer

Experience: 4-8 years

Job Summary

Develop machine-learning models to identify fraudulent transactions and suspicious financial activities.

Key Responsibilities

• Develop fraud detection and anomaly detection models.
• Analyze transaction and customer behaviour.
• Build real-time fraud scoring systems.
• Work with data engineering teams to process high-volume transaction data.
• Monitor model performance and false-positive rates.
• Develop predictive models for emerging fraud patterns.

Desired Candidate Profile

Mandatory Skills: Python, Machine Learning, SQL, Pandas, Scikit-learn Good to Have: PySpark, Kafka, real-time analytics, fraud/AML experience.