PAVAN SAI KUPPANNAGARI
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science with less than a year in Data Analytics & Machine Learning.
Entry-level Data Analyst and Data Science Enthusiast with hands-on experience in Data Analytics using Python, SQL, Power BI, NLP, Computer Vision and Predictive Analytics. Strong foundation in Python-based analytics, data preprocessing, dashboard development, business intelligence reporting, Machine Learning and model optimization with experience in building end-to-end analytical solutions and Streamlit deployment. Passionate about building data-driven solutions and continuously learning modern AI technologies.
Sri Sivani college of Engineering
Bachelor of Technology
August 1, 2021 – June 30, 2025
Sri Chaitanya Junior College
M.P.C Stream
June 1, 2019 – May 31, 2021
Fabric Defect Detection
January 1, 2026 – January 8, 2026
Designed a computer vision ML pipeline using OpenCV to detect textile anomalies, with Decision Tree achieving the highest F1-score across all evaluated models; hosted through Streamlit. Improved model F1-score through iterative hyperparameter optimization, directly reducing quality-control failure rates in a manufacturing simulation scenario.
View ProjectNetwork – Anomaly Prediction
December 4, 2025 – December 23, 2025
Engineered a Gradient Boosting classifier on real network traffic features, achieving high predictive performance; an effective model for detecting intrusion and abnormal-load events. Reduced false negatives to zero through systematic hyperparameter tuning (max_depth), making the model production-viable for live traffic monitoring. Integrated ML models into a Streamlit application for interactive prediction and real-time monitoring.
View ProjectCyberBully Detection
December 1, 2025 – June 1, 2026
Developed an NLP-based text classification solution for cyberbullying detection using supervised ML algorithms; achieved best performance with Decision Tree surpassing Naive Bayes, Logistic Regression, KNN & Random Forest Classifier on social media datasets achieving 99.45% accuracy. Deployed the solution using Streamlit with a user-friendly interface for live text prediction.
View ProjectEmployee Management System
November 1, 2025 – November 11, 2025
Architected a normalized relational database schema with 8+ tables; wrote 20+ optimized SQL queries using Joins, Subqueries and Aggregations, reducing ad-hoc reporting query time by ~45%.
Job Market Analysis
October 1, 2025 – June 1, 2026
Scraped and cleaned 500+ job listings using BeautifulSoup + Requests; identified top in-demand skills and salary trends through structured EDA. Produced visual insight reports with Matplotlib and Seaborn, surfacing actionable patterns in industry demand, tech stack preferences, and location-based hiring signals.
View ProjectBank Customer Segmentation
September 30, 2025 – October 12, 2025
Delivered 4 interactive KPI dashboards in Power BI analyzing demographic and transactional data across customer segments, enabling data-driven marketing and retention decisions. Implemented Row-Level Security (RLS) to restrict data visibility by stakeholder role, ensuring compliance and data governance. Built end-to-end Power Query transformation pipelines and DAX measures to automate reporting, cutting manual analysis time.
View ProjectData Science & Analytics
VitalSkills (Techkriti IIT Kanpur)
June 1, 2026 – Present
Python Programming
CODEC Technologies
June 1, 2026 – Present
Web Development Internship
Skill Vertex
June 1, 2026 – Present
Data Science & Gen AI
Innomatics Research Labs
July 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in diverse applications of data science, from business intelligence (Bank Customer Segmentation) to cybersecurity (Network Anomaly Prediction) and content moderation (CyberBully Detection). This breadth of interest and continuous learning (evidenced by certifications) suggests a good cultural fit for an organization that values innovation and continuous skill development. The focus on deploying solutions via Streamlit also indicates a practical, user-centric approach.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on delivering actionable insights. The emphasis on reducing false negatives in anomaly detection and improving F1-scores suggests an attention to detail and a results-oriented mindset. However, without direct work experience, it's difficult to assess operational fit in a team environment or under professional pressure.