Vamshi Paripelli

Results-oriented Computer Science Engineering student proficient in Python, Pandas, NumPy, Tableau, and Machine Learning. Spearheaded a real-world ML project, achieving R² = 0.93 through meticulous data preprocessing, feature engineering, and rigorous model evaluation. Eager to leverage analytical prowess as a Data Analyst at Franqlin Tech Systems (Softurecs AI Labs), driving actionable insights to empower AI-powered decision-making.

Résumé, links and contact below

About

Education

B.Tech — Computer Science & Engineering

Vaagdevi College of Engineering, Warangal, Telangana

Earned B.Tech in Computer Science & Engineering, specializing in advanced algorithms, data structures, and software engineering. Coursework emphasized practical application in areas like machine learning and scalable web development. Led a capstone project to design and implement a full-stack inventory management system using React, Node.js, and MongoDB, optimizing data processing efficiency by 30%. This experience honed my analytical, problem-solving, and robust software development skills, preparing me for impactful roles in technology.

Skills

Python

✦

Pandas

✦

NumPy

✦

Matplotlib

✦

Seaborn

✦

Scikit-learn

✦

CatBoost

✦

Ridge Regression

✦

EDA

✦

Data Cleaning

✦

Feature Engineering

✦

Data Preprocessing

✦

Statistical Analysis

✦

Tableau

✦

Matplotlib

✦

Seaborn

✦

Dashboard creation

✦

KPI reporting

✦

Chart design

✦

Regression

✦

Classification

✦

Model Evaluation (R²)

✦

Model Evaluation (RMSE)

✦

VS Code

✦

Git

✦

GitHub

✦

Excel

✦

HTML

✦

CSS

✦

Analytical Thinking

✦

Data-Driven Problem Solving

✦

Quick Learner

✦

Team Collaboration

✦

Detail-Oriented

✦

Communication Skills

✦

Python

✦

Pandas

✦

NumPy

✦

Matplotlib

✦

Seaborn

✦

Scikit-learn

✦

CatBoost

✦

Ridge Regression

✦

EDA

✦

Data Cleaning

✦

Feature Engineering

✦

Data Preprocessing

✦

Statistical Analysis

✦

Tableau

✦

Matplotlib

✦

Seaborn

✦

Dashboard creation

✦

KPI reporting

✦

Chart design

✦

Regression

✦

Classification

✦

Model Evaluation (R²)

✦

Model Evaluation (RMSE)

✦

VS Code

✦

Git

✦

GitHub

✦

Excel

✦

HTML

✦

CSS

✦

Analytical Thinking

✦

Data-Driven Problem Solving

✦

Quick Learner

✦

Team Collaboration

✦

Detail-Oriented

✦

Communication Skills

✦

Things I have built

Food Delivery Time Prediction — Data Analysis & ML

Conducted full EDA on delivery dataset covering traffic, weather, distance, and order type variables. Applied feature engineering and data preprocessing to improve model input quality. Benchmarked CatBoost, HistGradientBoosting, and Ridge Regression models; selected Ridge for best performance. Achieved R² = 0.93 — demonstrating strong model tuning, evaluation, and interpretation skills. Generated visual reports of model performance for business-level interpretation.

PythonScikit-learnPandasNumPyEDACatBoostHistGradientBoostingRidge Regression

E-Learning Platform Credibility & Engagement Analysis

Built a Python-based analytical system to evaluate content credibility and learner engagement patterns. Designed data models and UML diagrams; developed modules for data processing and performance analysis. Identified actionable insights: flagged low-credibility content and predicted learner drop-off risk. Outcome: Improved platform content quality and active learner retention metrics.

PythonMLData Analysis

Certifications

Programming Essentials in Python

CISCO

AI/ML

Infosys Springboard

Tableau

Simplilearn

Let’s make something good.

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