Opening Summary

We are looking for a Data Science & Analytics Intern who is passionate about turning data into meaningful insights. You will work closely with product, engineering, and business teams to analyze datasets, build predictive models, generate dashboards, and support data-driven decision-making across the organization.

Requirements

• Strong understanding of basic statistics, probability, and data analysis.
• Hands-on experience with Python or R for data manipulation and visualization.
• Ability to work with SQL for querying and data extraction.
• Familiarity with Jupyter Notebook, Google Colab, or similar tools.
• Must be available full-time for the full 6-month internship duration.
• Must share GitHub/portfolio/notebook with at least one analytics or ML project.

Responsibilities

• Collect, clean, and transform structured and unstructured data for analysis.
• Explore datasets to identify trends, patterns, and correlations.
• Build statistical models, basic ML models, or forecasting models.
• Create dashboards and visualizations using tools such as Power BI, Tableau, or Python libraries.
• Support A/B experiments, KPI analysis, and business reporting.
• Document analytical findings and present insights to stakeholders.
• Stay updated with new analytics techniques, visualization methods, and data tools.

Preferred Qualification

Experience with Tableau, Power BI, or Looker. Exposure to machine learning using Scikit-Learn. Understanding of business analytics, A/B testing, or KPI measurement. Familiarity with cloud platforms (AWS/GCP) for data workflows. Coursework or certifications in Data Science, BI, or ML.

Benefits

• Hands-on experience with real-world data projects
• Mentorship from experienced Data Scientists and Analysts
• Certificate of Completion
• Potential full-time opportunity based on performance

Stipend Eligibility Criteria

• Complete the full 6-month duration without early exit.
• Maintain minimum 80% attendance (as per company policy).
• Meet analytical deliverables including dashboards, reports, and model outputs.
• Actively participate in project discussions, reviews, and presentations.
• Adhere to ethical data handling, confidentiality, and organizational policies.
• Early resignation or termination due to performance/disciplinary issues will void stipend eligibility.