Data Analyst

• Collect, analyze, and interpret data from various internal and external sources to support business decision-making.
• Develop and maintain reports, dashboards, and data visualizations using tools such as Power BI, Tableau, or Amazon QuickSight.
• Perform data extraction and analysis using SQL, Microsoft Excel, and Python.
• Clean, transform, and validate data to ensure data accuracy, consistency, and quality.
• Identify trends, patterns, anomalies, and business opportunities through data analysis.
• Translate business requirements into data analysis, reports, and actionable insights.
• Perform ad-hoc analysis to support business and management needs.
• Collaborate with every stakeholder to understand business requirements and provide data-driven solutions.
• Prepare and present analytical findings and recommendations to management and relevant stakeholders.
• Support the development and improvement of data analytics processes, reporting standards, and data governance.
• Ensure data and analytical outputs are properly documented and maintained.

Qualifications

• Bachelor’s degree in Information Systems, Computer Science, Statistics, Mathematics, Economics, or a related field.
• Minimum 1–3 years of experience as a Data Analyst or in a related data/analytics role.
• Strong proficiency in SQL and Microsoft Excel.
• Experience with Power BI, Tableau, Amazon QuickSight, or other data visualization tools.
• Good knowledge of Python for data analysis is preferred.
• Strong understanding of data analysis, data cleaning, data visualization, and reporting.
• Good understanding of databases, data structures, and basic ETL/ELT processes.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to translate business requirements into data analysis and actionable insights.
• Good communication and presentation skills.
• Ability to work independently as well as collaboratively with cross-functional teams.

Preferred Skills

• Experience in financial services, banking, or consumer finance is a plus.
• Experience with DWH, Data Lake, ETL/ELT, or cloud platforms is a plus.
• Knowledge of statistical analysis and predictive analytics is a plus.
• Experience working with large datasets is preferred.