bhuvanesh

Chennai 0+ yrs exp 70 · Very Good

About

Analytical B.E. Computer Science Graduate (2026) with dual internship experience building automated ETL pipelines and executive Business Intelligence dashboards. Proven capability utilizing SQL, Python, and Power BI to optimize data pipelines, detect cost anomalies, and translate complex relational databases into actionable business strategies.

Skills & Expertise (22)

Data Cleansing Intermediate

6.0/10

0.2

Years Exp

NumPy Intermediate

6.0/10

0.2

Years Exp

Python Intermediate

6.0/10

0.2

Years Exp

Pandas Intermediate

6.0/10

0.2

Years Exp

MySql Beginner

4.2/10

0.2

Years Exp

Postgresql Beginner

4.2/10

0.2

Years Exp

SQL Beginner

4.2/10

0.2

Years Exp

Joins Beginner

4.2/10

0.2

Years Exp

Power BI Beginner

4.2/10

0.2

Years Exp

Microsoft Excel Beginner

4.2/10

0.2

Years Exp

GitHub Beginner

4.2/10

0.2

Years Exp

Git Beginner

4.2/10

0.2

Years Exp

Feature Engineering Beginner

2.8/10

0.2

Years Exp

ETL Processes Beginner

2.8/10

0.2

Years Exp

Tableau Beginner

2.8/10

0.2

Years Exp

VLOOKUP Beginner

2.8/10

0.2

Years Exp

Advanced Pivot Tables Beginner

2.8/10

0.2

Years Exp

Schema Validation Beginner

2.8/10

0.2

Years Exp

CTEs Beginner

2.8/10

0.2

Years Exp

Window Functions Beginner

2.8/10

0.2

Years Exp

Exploratory data analysis EDA

Work Experience

Machine Learning & AI Intern

Tamizhan Skills

Dec 2025 - Jan 2026

Engineered data preprocessing pipelines featuring scaling and categorical encoding, cutting dataset training anomalies. Developed and cross-validated classification models to track operational patterns, maintaining model accuracy baselines. Designed interactive dashboards and visual tracking tools in Power BI to present key predictive insights to department leads.

Data Science Intern

Trios Technologies

Jul 2024 - Aug 2024

Validated and cleaned 40,000+ unstructured records using Python (Pandas/NumPy), improving base dataset accuracy by 18%. Automated data preparation workflows, cutting manual processing effort by 5 hours per week and speeding up reporting cycles. Executed exploratory data analysis to isolate missing entries and anomalous records, reducing system pipeline errors.