Opportunity brief
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.