Key Responsibilities
Extract, clean, transform, and analyze large datasets using Python and SQL to generate business-ready insights
Build and maintain automated analytical workflows, reports, and scheduled emailers for business stakeholders
Develop reusable data processing scripts and frameworks to support recurring analyses
Perform retail-focused analyses including:
o Best deal / promotion effectiveness
o Size & assortment mix analysis
o Sales, inventory, and demand trend analysis
Convert analytical outputs into clear narratives, summaries, and visualizations for senior stakeholders
Partner with business teams to understand requirements and translate them into analytical solutions
Ensure data quality, validation checks, and performance optimization across pipelines
and reports
Required Skills & Experience
3–5 years of experience in Data Analysis / Analytics Engineering
Strong proficiency in Python, with advanced usage of Pandas
Strong SQL skills for complex querying and data analysis
Excellent logic building and problem-solving abilities
Proven experience working in or supporting the retail / consumer business domain
Ability to convert data into insightful, decision-oriented outputs
Technical Stack
Programming & Data Processing
Python
Pandas
SQL
Data Analysis & Visualization
Exploratory Data Analysis (EDA)
Matplotlib
Data validation and insight reporting
Automation & Tools
Outlook automation using win32com
Scheduled reporting and automated emailers
Libraries: tqdm, datetime, os, PIL
Version Control
Git / GitHub / GitLab