Kiran kumar swain

Berhampur, Odisha 0+ yrs exp 76 · Very Good

About

Recent B.Tech Computer Science graduate skilled in Python, SQL, Data Analytics, Machine Learning, Power BI, Excel, and Business Intelligence. Completed 3+ projects across sales analytics, health prediction, and student burnout detection. Experienced in data cleaning, exploratory data analysis, dashboard development, KPI reporting, feature analysis, model training, model evaluation, and Streamlit application development.

Skills & Expertise (39)

Python Advanced

8.1/10

Years Exp

NumPy Advanced

8.0/10

Years Exp

Pandas Advanced

8.0/10

Years Exp

SQL Intermediate

7.6/10

Years Exp

scikit-learn Intermediate

7.5/10

Years Exp

Power BI Intermediate

7.4/10

Years Exp

Data Visualization Intermediate

7.0/10

Years Exp

DAX Intermediate

6.5/10

Years Exp

ETL Intermediate

6.5/10

Years Exp

Git Intermediate

6.0/10

Years Exp

Joins VS Code Aggregations GROUP BY Having Clause LLMs agentic AI AI Agents Retrieval-Augmented Generation Prompt Engineering GitHub Jupyter Notebook Conditional Formatting Power Query Data Modeling KPI Reporting Dashboard Development Advanced Excel Pivot Tables VLOOKUP XLOOKUP MySql Data Cleaning EDA Business Analysis Classification Regression Model Training Model Evaluation

Work Experience

AI & Data Analytics Intern

Rooman Technologies Pvt. Ltd.

Feb 2026 - May 2026

Analyzed 3+ structured datasets using Python, Pandas, NumPy, Excel, SQL, and Power BI to identify trends, patterns, and business insights. Cleaned and transformed raw data across 4+ project tasks using preprocessing, visualization, KPI reporting, and dashboarding techniques. Improved business reporting by analyzing prediction results, performance metrics, and error patterns across 4+ analytics tasks.

Machine Learning Summer Training Program

PMEC, Berhampur

Jun 2023 - Jul 2023

Practiced 5+ ML concepts including preprocessing, train-test split, classification, regression, prediction analysis, and model comparison. Built and optimized classification and regression models using Scikit-learn, comparing algorithm performance through validation techniques and predictive analysis.