Intern - Business Analytics

About the Role

Data Analytics Intern

6-month full-time internship

Key Responsibilities

Data Cleaning & Preparation:

Ad-hoc Analysis:

Dashboard Development:

Project Support:

Automation:

Reporting:

Qualifications

Required:

Bachelor’s degree (B.Sc./B.Tech/B.E.) in any Science stream or Engineering (Mathematics must be one of the subjects studied)

Strong foundation in mathematics and statistics

Proficiency in SQL for data extraction and manipulation

Working knowledge of Python (pandas, numpy, matplotlib/seaborn)

Advanced Microsoft Excel skills (pivot tables, VLOOKUP, formulas)

Experience with Tableau or willingness to learn quickly

Strong problem-solving skills and attention to detail

Excellent communication skills to present findings to non-technical stakeholders

Good to Have:

Prior internship or project experience in data analytics

Understanding of basic statistical concepts and A/B testing

Familiarity with healthcare, retail, or e-commerce domains

Experience with data automation and scripting

Knowledge of Git for version control

What You’ll Learn

Real-world application of data analytics in a high-growth healthcare startup

Experience working with large-scale retail and e-commerce datasets

Building production-grade dashboards and automated reporting systems

Collaborating with cross-functional teams in a fast-paced environment

Business acumen in the pharmacy and healthcare sector

Work Arrangement

Location:

Duration:

Conversion:

Technical Skills

SQL:

Proficiency in writing complex queries, joins, subqueries, and data manipulation (SELECT, WHERE, GROUP BY, HAVING, etc.)

Python:

Working knowledge of Python for data analysis including:

Data manipulation libraries (pandas, numpy)

Data visualization libraries (matplotlib, seaborn)

Basic scripting and automation

Microsoft Excel:

Advanced proficiency including:

Pivot tables and pivot charts

Complex formulas (VLOOKUP, INDEX-MATCH, IF statements)

Data cleaning and transformation

Basic macros (preferred)

Tableau:

Ability to create interactive dashboards and visualizations (or strong willingness to learn)

Statistics:

Understanding of basic statistical concepts (mean, median, standard deviation, correlation, distributions)

Data Cleaning:

Experience with data validation, handling missing values, outlier detection, and data transformation