Sarankumar S

AI & Data Science undergraduate

Coimbatore, Tamil Nadu 0+ yrs exp 80 · Excellent

About

AI & Data Science undergraduate with hands-on experience in Data Analytics and Business Intelligence. Skilled in SQL, Python, Power BI and ETL pipelines, with a strong ability to understand business problems and transform complex data into actionable insights and impactful dashboards.

Skills & Expertise (42)

Python Intermediate

8.1/10

Years Exp

Power BI Intermediate

8.0/10

Years Exp

Pandas Intermediate

8.0/10

Years Exp

Exploratory data analysis Intermediate

8.0/10

Years Exp

Excel Intermediate

7.5/10

Years Exp

Teamwork Intermediate

7.5/10

Years Exp

Data Cleaning Intermediate

7.5/10

Years Exp

Data Storytelling Intermediate

7.0/10

Years Exp

NumPy Intermediate

7.0/10

Years Exp

MySql Intermediate

7.0/10

Years Exp

VS Code Stakeholder Management Jupyter Notebook GitHub Google Sheets Microsoft PowerPoint Microsoft Word ETL Matplotlib Cross-Functional Communication Data-driven decision making Problem Solving KPI Tracking Attention to Detail Window Functions Pivot Tables Power Query XLOOKUP INDEX MATCH Preprocessing Statistical Analysis CTEs Excel Charts Joins Subqueries Aggregations Data Extraction Transformation validation DAX Data Modeling

Work Experience

Data Analyst Intern

TheSmartBridge

Oct 2025 - Nov 2025

Engineered an end-to-end pipeline using Power BI, Power Query, and DAX across 6 datasets with 50,000+ records, achieving 96% data quality and reducing query response time by 45%. Built an interactive Business Intelligence (BI) dashboard with 25+ visualizations for global energy trends across 195+ countries, leading dashboard development to enable real-time KPI tracking.

Data Analyst Intern

Vodafone Idea Foundation

Sep 2025 - Oct 2025

Interpreted and analyzed 100,000+ Airbnb booking records using exploratory data analysis (EDA) with Python, Pandas, and Seaborn to identify seasonal pricing trends, demand concentration patterns, and revenue optimization opportunities. Analyzed 10,000+ Netflix titles across 190+ countries using ML clustering and regression, uncovering audience behavior trends and delivering insights for content strategy and international market expansion.