Responsibilities of the Intern:

• Assist in collecting, cleaning, and structuring large datasets from internal and external sources.
• Support business and product teams with data-driven insights.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Contribute to dashboards and reports used by leadership for decision-making.
• Work with data engineers and developers to improve data quality and reliability.
• Prepare visualizations that simplify complex information for non-technical stakeholders.
• Participate in regular standups, sprint planning, and documentation tasks.
• Support A/B testing, user behavior analysis, and performance metrics tracking.
• Clean and preprocess raw data using Python, SQL, or analytical tools.
• Build and maintain dashboards in tools like Power BI, Tableau, or Looker Studio.
• Write efficient SQL queries to answer business questions.
• Automate repetitive data tasks (reports, daily metrics).
• Analyze KPIs such as user engagement, retention, campaign performance.
• Document datasets, schemas, data flows, and analysis results.
• Ensure data accuracy, consistency, and security across systems.
• Collaborate with cross-functional teams (tech, product, growth, marketing).

Requirements:

• Strong knowledge of Python (Pandas, NumPy) or R for data manipulation.
• Hands-on SQL experience (PostgreSQL preferred).
• Understanding of statistics, probability, and analytical concepts.
• Ability to create charts, dashboards, and reports.
• Good Excel/Google Sheets skills.
• Ability to translate data outcomes into insights.
• Strong attention to detail and problem-solving skills.
• Knowledge of ETL pipelines and data warehousing concepts.
• Familiarity with APIs and JSON data structures.
• Experience with Git, version control, JIRA/Notion, or Agile methodologies.
• Understanding of machine learning basics (regression, clustering, classification).
• Knowledge of tools like Matplotlib, Seaborn, Plotly, or Power BI.