Data Analyst

Role Description:

The Data Analyst is responsible for collecting, organizing, and interpreting data to deliver insights that support strategic decision-making and business operations. This role works closely with cross-functional teams to analyze trends, identify patterns, and produce meaningful reports that help improve performance, optimize processes, and guide organizational planning.

Key responsibilities include gathering data from multiple sources, cleaning and validating datasets, and performing quantitative and qualitative analysis. The Data Analyst develops dashboards, visualizations, and reports to communicate findings clearly to both technical and non-technical stakeholders. This may involve building automated reporting tools, conducting ad-hoc analyses, and tracking KPIs to measure business outcomes.

The role also supports forecasting, monitoring data accuracy, and evaluating business processes to recommend improvements. A strong analytical mindset, attention to detail, and proficiency in data tools are essential. The Data Analyst collaborates closely with teams across finance, marketing, operations, product, and management to ensure data-driven decision-making throughout the organization.

Qualifications:

• Bachelor’s degree in

  Data Science

  ,

  Statistics

  ,

  Mathematics

  ,

  Computer Science

  ,

  Economics

  ,

  Business

  , or a related field.
• Strong analytical and problem-solving skills with the ability to interpret complex datasets.
• Proficiency in data tools such as

  Excel

  ,

  SQL

  ,

  Python

  ,

  R

  ,

  Tableau

  , or

  Power BI

  .
• Experience in data cleaning, data validation, and data visualization.
• Ability to prepare clear and concise reports, dashboards, and presentations.
• Understanding of statistical methods, forecasting techniques, and performance metrics.
• High attention to detail and strong organizational skills when managing large datasets.
• Excellent communication skills, with the ability to explain insights to stakeholders in a simple and actionable way.
• Ability to work collaboratively in cross-functional teams and manage multiple priorities.
• Familiarity with data pipelines, ETL processes, or database management is a plus.
• Curiosity, willingness to learn, and a proactive approach to identifying data-driven improvements.