Data Analyst Internship
TalentCV
RemoteFresher1h agovia Unstop
This job at a glance
- Who can apply
- Freshers and up to 1 year
- Must know
- Data analysisData visualizationStakeholder managementAgileStatisticsPython
- Nice to have
- SQLPostgreSQL
- Work
- Remote · internship
- Pay
- ₹7,000/month
- Skill demand
- Data analysis87%Data visualization69%Stakeholder management31%of 111 similar fresher jobs posted in India this week
- Listed
- 1 Nov 2026 · still open
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Key Responsibilities
- 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 & Tech Stack
- 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.