Data Analytics Graduate - Python - SQL - Visualization

BHARATH KUMAR

Khammam, Telangana ******************@*****.*** +91-760******* LinkedIn: linkedin.com/in/bharathkumar GitHub: github.com/bharathkumar

SUMMARY

Detail-oriented B.Tech Computer Science graduate (CGPA: 8.58/10) with hands-on experience in data analysis, Python (Pandas, NumPy, Matplotlib), SQL, Excel, and data visualization. Skilled in data cleaning, EDA, statistical analysis, and translating data insights into actionable business recommendations. Strong communicator with a proven track record of managing large datasets with 95%+ accuracy.

TECHNICAL SKILLS

Data Analysis & EDA: Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn), Statistical Analysis, Hypothesis Testing

Databases & Querying: SQL (MySQL, PostgreSQL, MS SQL Server), LINQ, writing complex queries, joins, aggregations, stored procedures

Visualization: Tableau (basic), Power BI (basic), Chart.js, Matplotlib, Seaborn, MS Excel (Pivot Tables, VLOOKUP, Charts)

Tools & Platforms: Jupyter Notebook, Google Colab, Git/GitHub, MS Excel, Google Sheets, VS Code

Other: Data Cleaning, Feature Engineering, Regression, Classification, A/B Testing, Report Writing, Dashboard Design

EDUCATION

B.Tech – Computer Science CGPA: 8.58/10 Kakatiya University College of Engineering & Technology, Warangal 2021 – 2025

•Relevant Coursework: Statistics & Probability, DBMS, Machine Learning, Data Structures & Algorithms, Python Programming, Linear Algebra

PROJECTS

OTT Content Analytics – EDA & Predictive Modelling Academic Project 2024

•Performed end-to-end EDA on 5,000+ movies/shows dataset (Netflix, Prime Video, Disney+) using Python — cleaned missing values, engineered features (content age, genre tags), and identified genre & rating trends

•Built a Random Forest classifier to predict content ratings (G/PG/R) achieving 82% accuracy; evaluated with precision, recall, F1-score; visualized feature importances and decision boundaries

•Produced a structured insights report with actionable recommendations on content performance, presented using Matplotlib/Seaborn visualizations

Data Quality & Validation Pipeline Academic & Self-Initiated 2023 – 2024

•Designed a Python-based validation pipeline using Pandas and regex to process 1,000+ records, detecting duplicates, null values, and schema errors with 95%+ detection accuracy

•Automated reporting with Matplotlib summary charts and Excel exports (openpyxl), reducing manual review effort by ~40% and generating audit-ready documentation for stakeholders

SQL Analytics – Student & Inventory Database Academic Project 2024

•Wrote complex SQL queries (joins, window functions, CTEs, subqueries) across relational schemas to extract KPIs including enrollment trends, inventory turnover, and grade distributions

•Built Excel-based interactive dashboards using Pivot Tables, slicers, and conditional formatting to present findings clearly to non-technical stakeholders

CERTIFICATIONS

Python for Data Science – Coursera/NPTEL SQL for Data Analysis – Mode Analytics Data Visualization – IBM/Kaggle Google Data Analytics – Coursera (add actual certs)

KEY STRENGTHS

EDA & Statistical Analysis Python & SQL Data Cleaning & Wrangling Dashboard & Visualization Business Insight Communication Attention to Detail Fast Learner Documentation

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