Assistant Manager - Retail Analytics

About the role

The Retail Risk Analytics Unit of Emirates Islamic Bank supports Consumer Risk Management through portfolio analytics, risk modelling, management information and regulatory reporting. It provides actionable insights on portfolio performance and emerging risks, and works with Business, Collections, Finance and Technology to improve analytical capabilities through automation and modern data tools.

Key responsibilities

• Support the migration of existing analytics and reporting processes to Python, developing reusable scripts and automated workflows.
• Analyse retail portfolio performance (delinquency, vintage, roll rates, segmentation, collections trends) and recommend actions.
• Monitor application and behavioural scorecards and support statistical and predictive models for retail credit risk and collections.
• Maintain code quality through Git and GitHub, including version control, testing, documentation and peer reviews.
• Help colleagues adopt Python-based processes through knowledge sharing and technical guidance.
• Prepare management and regulatory reports with accurate data, reconciliations and timely delivery.
• Ensure analytical solutions and models comply with the Bank's model governance requirements.

Required profile

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, Finance or a related quantitative discipline.
• At least 3 years of experience in data analytics, risk analytics or analytical automation, including at least 2 years of hands-on Python development.
• Practical experience developing automated analytical workflows and migrating reporting processes to Python.
• Ability to write reusable, maintainable code and perform data reconciliation, testing and quality checks.
• Strong analytical, problem-solving and communication skills, with the ability to share technical knowledge.

Required skills

• Strong Python and SQL, including Pandas and NumPy.
• Proficiency in Git and GitHub, including version control, collaborative development and code reviews.
• Working knowledge of statistics and predictive modelling.