Data Analyst

Role overview

This position is for a Data Analyst who will help drive informed business decisions through collecting, organizing, analyzing, and interpreting data. The role focuses on turning raw information into clear insights that improve performance, support reporting, and strengthen operational efficiency.

You will work with data from different sources, clean and validate datasets, and use spreadsheets and analytical tools to spot trends, patterns, and anomalies. The role also includes preparing dashboards, summaries, and reports that can be understood by both technical and non-technical audiences.

Key responsibilities

• Gather information from multiple sources and prepare it for analysis
• Clean, structure, and verify datasets to maintain data quality
• Examine data to uncover trends, patterns, and useful findings
• Track performance indicators and support ongoing metric reporting
• Create or assist with dashboards, summaries, and analytical reports
• Identify irregularities in data and help resolve inconsistencies
• Carry out basic exploratory and descriptive analysis
• Record methods, assumptions, and key conclusions clearly
• Work with different teams on data requests and project needs
• Improve reporting processes and overall data reliability
• Explain findings in a clear and practical way for stakeholders

Qualifications and skills

The ideal candidate should have strong analytical ability, solid attention to detail, and a structured way of solving problems. Comfort with spreadsheets and basic analytical tools is important, along with the ability to manage several data tasks at once.

Good written and verbal communication is needed to translate data findings into understandable recommendations. Familiarity with data visualization or reporting tools is an advantage. A background in Data Analytics, Statistics, Economics, Business, or a related discipline is preferred.

Work style

This role involves collaboration with cross-functional teams while also requiring the ability to work independently when needed. A willingness to learn new tools, methods, and datasets is important for success in this position.