Senior Data Scientist📣 إعلان

About Rasēd and the Role

Rasēd | راصد is a cutting-edge solution for fraud detection and prevention, designed for financial institutions, fintechs, and payment providers. Our platform integrates AI, device intelligence, and behavioral biometrics to detect and prevent fraud in real time, ensuring a seamless user experience. It also provides advanced analytics for post-incident investigation, compliance, and automated case management. We are seeking a Senior Data Scientist to join our team in Riyadh.

Role Overview

The Senior Data Scientist will be responsible for building and enhancing the models and rules that detect fraud, AML risk, and various financial crimes, from transaction monitoring to mule activity and account takeover. This role involves end-to-end ownership of fraud analytics components, encompassing data exploration, deployment, and monitoring. The successful candidate will work closely with fraud, compliance, and engineering teams to deliver robust solutions. This full-time position requires 5-10 years of relevant experience.

Key Responsibilities

• Contribute to the development and deployment of fraud detection, AML, and financial crime prevention solutions.
• Build and improve models and rules that detect suspicious behavior, transaction fraud, mule activity, account takeover, sanctions risk, and abnormal customer patterns.
• Translate fraud, compliance, and business requirements into practical analytical solutions, detection scenarios, dashboards, and workflows.
• Own defined fraud analytics components end-to-end, from data exploration and feature engineering to testing, deployment, and monitoring.
• Work with structured financial, customer, device, transaction, and case-management data to identify fraud patterns and risk indicators.
• Conduct experimentation and optimization of fraud detection models, risk scoring logic, and scenario thresholds.
• Support model deployment and monitoring in collaboration with engineering teams, ensuring fraud models remain accurate, explainable, and operationally useful.
• Assist in tuning fraud scenarios, reducing false positives, improving detection rates, and measuring model effectiveness.
• Interact with SME clients under guidance to understand fraud use cases, operational pain points, and regulatory expectations.
• Stay updated with fraud trends, AML typologies, regulatory requirements, and industry best practices.

Required Qualifications and Experience

• 5-10 years of experience in a data science or analytics role, preferably within fraud detection, AML, or financial crime.
• Hands-on Python experience.
• Experience or strong exposure to fraud detection, AML, risk analytics, transaction monitoring, or financial crime.
• Strong proficiency in SQL and experience working with structured data.
• Experience working with data such as transactions, customer profiles, device data, alerts, cases, or financial records.

Essential Skills and Knowledge

• Familiarity with feature engineering, data pipelines, model training, model evaluation, and deployment workflows.
• Understanding of fraud detection concepts such as anomaly detection, risk scoring, false positives, behavioral patterns, mule accounts, and suspicious activity monitoring.
• Strong analytical thinking and the ability to connect data patterns to real-world fraud behavior.
• Strong communication skills and the ability to explain technical findings to business, fraud, and compliance teams.

Work Environment

This is a full-time position based in Riyadh, Saudi Arabia. The role offers an opportunity to contribute to advanced fraud detection and prevention technologies within a specialized team.