Junior Data Analyst

Role Overview

Key Responsibilities

• Collect, clean, validate, and organize data from multiple internal and external sources.
• Analyze large datasets to identify trends, patterns, anomalies, and business opportunities.
• Perform data reconciliation and investigate discrepancies to ensure accuracy and consistency.
• Interpret data and translate findings into meaningful business insights.

• Prepare and maintain daily, weekly, and monthly business performance reports.
• Develop and maintain interactive dashboards using Power BI or Tableau.
• Track and analyze key business metrics, including revenue, clicks, conversions, transactions, and campaign performance.
• Ensure timely and accurate delivery of reports to relevant stakeholders.

• Analyze affiliate marketing, publisher, advertiser, cashback, and e-commerce performance data.
• Monitor KPIs and highlight significant performance changes, trends, and deviations.
• Support business teams with data-driven insights to improve operational efficiency and performance.
• Assist in identifying gaps and opportunities through regular data analysis.

• Work with cross-functional teams to understand business requirements and reporting needs.
• Identify opportunities to automate repetitive reporting and data-processing tasks.
• Maintain proper documentation of data sources, reports, dashboards, and analytical processes.
• Support ad hoc data requests and analysis as required by the business.

Required Skills & Qualifications

• Bachelor's degree in Statistics, Mathematics, Computer Science, Data Analytics, Economics, or a related field.
• 0–2 years of experience in Data Analytics, MIS, Business Analytics, or a similar role.
• Strong proficiency in MS Excel or Google Sheets, including formulas, Pivot Tables, VLOOKUP/XLOOKUP, and data handling.
• Basic to intermediate knowledge of SQL, including SELECT, WHERE, JOIN, GROUP BY, and aggregate functions.
• Working knowledge of Power BI or Tableau for dashboard creation and data visualization.
• Strong analytical, logical reasoning, and problem-solving abilities.
• Good understanding of data validation, data cleaning, and reporting practices.
• Ability to interpret data and communicate findings clearly.
• High attention to detail and commitment to data accuracy.

Good to Have

• Basic knowledge of Python (Pandas, NumPy) for data analysis.
• Familiarity with Google Analytics or other web analytics platforms.
• Understanding of digital marketing, affiliate marketing, or e-commerce metrics.
• Exposure to handling large datasets and reporting automation.
• Basic understanding of statistical concepts and data visualization techniques.

Key Competencies

• Analytical and critical thinking.
• Strong numerical and logical reasoning.
• Attention to detail and accuracy.
• Structured problem-solving approach.
• Ownership and accountability.
• Effective communication and collaboration.
• Ability to manage multiple reporting requirements.
• Curiosity and willingness to learn new tools and technologies.