nagireddy Sudharshan reddy

0+ yrs exp 76 · Very Good

About

Graduate in Computer Science and Engineering with hands-on experience across the full software development life cycle, from requirement analysis and coding to testing and deployment. Proficient in Python and JavaScript, with a strong foundation in data structures, algorithms, OOP, DBMS, and operating systems. Skilled in building and debugging full-stack applications using React.js, Flask, and REST APIs, with practical exposure to ML tooling, MySQL database administration, and Git-based collaborative development. Certified in Data Science, ready to deliver production-quality, error-free code for enterprise client engagements.

Skills & Expertise (33)

Python Advanced

8.0/10

Years Exp

Seaborn Advanced

8.0/10

Years Exp

Matplotlib Advanced

8.0/10

Years Exp

NumPy Advanced

8.0/10

Years Exp

Pandas Advanced

8.0/10

Years Exp

Machine Learning Advanced

8.0/10

Years Exp

Adaptability Advanced

7.0/10

Years Exp

SQL Advanced

7.0/10

Years Exp

NLP Advanced

7.0/10

Years Exp

Deep Learning Advanced

7.0/10

Years Exp

Problem Solving Advanced

7.0/10

Years Exp

Communication Advanced

7.0/10

Years Exp

Teamwork Advanced

7.0/10

Years Exp

Time management Advanced

7.0/10

Years Exp

SDLC Intermediate

6.0/10

DBMS Intermediate

6.0/10

Oracle SQL Intermediate

6.0/10

Operating systems Intermediate

6.0/10

OOP Intermediate

6.0/10

Algorithms Intermediate

6.0/10

Data Structures Intermediate

6.0/10

Excel Intermediate

6.0/10

VS Code Intermediate

6.0/10

GitHub Intermediate

6.0/10

Git Intermediate

6.0/10

MongoDb Intermediate

6.0/10

REST APIs Intermediate

5.5/10

React JS Intermediate

5.5/10

JavaScript Intermediate

5.5/10

Flask Intermediate

5.0/10

CSS Intermediate

5.0/10

HTML Intermediate

5.0/10

AWS

Work Experience

Data Science Intern

The Skybrisk

Jan 2026 - Apr 2026

Architected a content-based movie recommendation engine using TF-IDF vectorization and cosine similarity across 5,000+ titles, improving recommendation relevance by 35%. Engineered end-to-end data preprocessing and feature-engineering pipelines for Telecom Churn and Netflix datasets spanning 10,000+ records, cutting EDA turnaround time by 40%. Delivered 6+ interactive dashboards using Matplotlib and Seaborn and applied supervised ML across 3 datasets, boosting prediction accuracy by 15% through iterative tuning. Automated a weekly data validation workflow across 4 pipeline stages using Python scripts, eliminating 6+ hours of manual QA effort per sprint and reducing data entry errors by 25%.