Company Description MUBEEN is an AI-driven fraud prevention intelligence ecosystem built for the MENA region, helping digital businesses detect and prevent fraud in real time. By combining advanced AI technologies with deep regional expertise and expert-led services, MUBEEN enables organizations to protect revenue and reduce operational and financial risk.
As MUBEEN continues to grow and expand its capabilities across the region, we are growing our team alongside it. We are looking for talented, driven people who want to help us build the next generation of fraud prevention solutions and contribute to our mission of creating lasting digital trust across MENA.
Our platform offers integrated, data-focused solutions that support secure digital growth and enable companies to respond quickly to evolving fraud threats. As we scale, we are building a team capable of delivering reliable, scalable, and intelligent fraud prevention capabilities to businesses across the region.
Role Description The Senior Data Scientist at MUBEEN will design, build, and maintain machine learning models and analytical frameworks that power real-time fraud detection across digital channels. In this full-time remote role, the individual will work closely with product, engineering, and fraud operations teams to analyze large-scale data, identify emerging fraud patterns, and translate insights into robust, production-ready solutions. Daily responsibilities include exploratory data analysis, model development and evaluation, feature engineering, experimentation, and performance monitoring of deployed models. The Senior Data Scientist will also contribute to data strategy, mentor other team members, and help define best practices for rigorous experimentation, model governance, and responsible AI within the fraud prevention ecosystem. Qualifications Strong skills in Data Science and Statistics, including experience with machine learning algorithms, hypothesis testing, and model evaluation. Proficiency in Data Analytics and Data Analysis for large, complex datasets, with the ability to uncover patterns, trends, and actionable insights. Experience in Data Visualization, using modern visualization tools or libraries to communicate findings clearly to technical and non-technical stakeholders. Advanced programming skills in Python or R, with hands-on experience in ML frameworks (e.g., scikit-learn, Tensor Flow, PyTorch) and SQL for data manipulation. Background in building and deploying models in production environments, ideally within fraud detection, risk scoring, or financial services. Familiarity with cloud-based data platforms and MLOps practices (e.g., CI/CD for models, monitoring, versioning, and model lifecycle management). Ability to collaborate effectively in remote, cross-functional teams and to communicate complex concepts in a clear, structured manner. Bachelor’s or Master’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Data Science, Engineering) or equivalent practical experience. Experience working with data from the MENA region or in fraud prevention, cybersecurity, or fintech is a strong plus.