Data Analyst (UAE National Only)

Overview

Key Responsibilities

• Data Analysis & Insight Generation Conduct exploratory and advanced data analysis on large-scale datasets, including credit and financial data, to identify trends, patterns, and actionable insights that support business and risk decisions.
• Collaboration with Data Science Work closely with Data Scientists to support partner insights generation, validation, and interpretation, ensuring analytical outputs are robust, explainable, and aligned to business needs.
• Ad-hoc Analysis & Business Support Own and deliver ad-hoc analytical requests from internal stakeholders, structuring ambiguous problem statements into clear analytical approaches and delivering timely, high-quality outputs.
• Data Preparation & Querying Extract, manipulate, and analyse data using SQL, Python, and other tools to create clean, structured datasets for analysis and reporting.
• Executive-Ready Reporting & Presentation Develop management-ready analytical reports and presentations, translating complex analysis into clear, concise narratives suitable for senior management, committees, regulators, and partners.
• Analytical Tools & Dataset Development Support the development and enhancement of analytical datasets, tools, and reusable frameworks to improve efficiency and consistency in analysis.
• Data Quality & Validation Perform data validation and quality checks to ensure accuracy, consistency, and reliability of analytical outputs.
• Performance Monitoring & Reporting Track and analyse key metrics, trends, and performance indicators, providing regular updates and insights to stakeholders.
• Cross-functional Collaboration Work closely with Data Engineering, BI, Product, and external partners to ensure data availability, usability, and alignment with analytical requirements.
• Documentation & Governance Document analytical methodologies, assumptions, and outputs to support transparency, reproducibility, and compliance with data procedures and supporting auditability and reproducibility
• The responsibilities and duties outlined above are not exhaustive and may evolve over time. The role may require additional tasks and responsibilities as assigned by the line manager or higher authorities, in alignment with organizational needs.

Education

• Bachelors or Master’s Degree in Statistics, Economics, Data Science, Mathematics, Engineering, or a related quantitative discipline
• Strong proficiency in statistical analysis
• Strong proficiency in Python (Pandas, NumPy, data manipulation and analysis) and SQL (advanced querying and data extraction)
• Strong proficiency in PySpark / Experience with Base SAS / SAS EG
• Proficiency in Microsoft Excel and PowerPoint for analysis and presentation
• Experience with data visualization tools (e.g., Power BI)
• Proficient in English

Experience

• 3 - 6 years of experience in data analytics or a related field
• Strong experience working with large, complex datasets, performing detailed analysis to extract meaningful insights
• Solid understanding of statistical analysis, data quality assessment, and analytical methodologies
• Strong understanding of analytical techniques, data exploration, and insight generation
• Exposure to working alongside Data Science teams and model-driven environments
• Experience supporting business stakeholders with both structured and ad-hoc analysis
• Experience producing management-ready analytical reports, dashboards, and insight summaries
• Working experience in cloud-based analytics environments, with Databricks strongly preferred.
• Knowledge of credit data, credit risk concepts, or market-wide analytics is highly desirable
• Exposure to working in regulated or data-governed environments is an advantage
• Strong analytical thinking and structured problem-solving capability, and convert analysis into actionable insights
• Comfortable explaining methodology, assumptions, and implications of analysis to non-technical audiences
• Confident in presenting insights and analytical outcomes, explaining methodology, assumptions, and implications to non-technical audiences
• High attention to detail and ownership of analytical outputs
• Ability to manage multiple analytical tasks and deliver high-quality outputs within agreed timelines
• Collaborative mindset, able to work effectively across internal teams, vendors, and partners without formal authority
• Able to deal with varied tasks and to work under pressure to meet deadlines and targets
• Strong attention to detail in ensuring high levels of accuracy and quality in all deliverables

Why Join Us?

• Opportunities for continuous learning, certifications, and professional development.
• Dedicated to building a diverse and inclusive workplace where everyone feels valued and empowered to be their authentic selves.
• Committed to building a stable, forward-thinking organization where innovation thrives.