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Patturi Pavan Kumar

Aspiring Data Analyst / Business Intelligence Analyst • p************************@gmail.com • +91*******439 • linkedin.com/••••• • drivetube.ai/•••••

Professional Summary

Data Analyst with 1+ years of internship and project experience applying Python, SQL, Power BI and machine learning to deliver actionable insights. Strong hands-on work with Pandas and NumPy for data cleaning and EDA, Scikit-learn for supervised modeling, and Matplotlib for model interpretation. Built interactive dashboards and reports using Power BI and Tableau to support marketing, e-commerce, and education analytics use cases. Experienced in designing ETL steps, writing SQL queries, and packaging models behind Flask endpoints for demo deployments. Demonstrated ability to shorten reporting cycles and translate analytics into stakeholder-ready dashboards. Seeking an entry-level Data Analyst / BI Analyst role to apply analytical rigor and dashboarding experience to business decision-making.

Technical Skills

Programming Language: Python,SQL
Frontend Technologies: HTML,CSS
Backend Technologies: Flask
Databases: MySQL
Version Control & Development Tools: GitHub
Data Analysis & Visualization: Pandas,NumPy,Matplotlib,Data Cleaning,Regression,Power BI,Tableau,Microsoft Excel
Machine Learning & AI: Classification,Model Evaluation
AI/ML Frameworks & Libraries: scikit-learn
MLOps: Feature Engineering

Work Experience

Besant Technologies
Data Science with GenAI Intern
June 2026 – Present
Internship focused on data cleaning, model prototyping and GenAI experimentation for training/demo datasets.
Tech Stack: Pandas, NumPy, Scikit-learn, Matplotlib, Flask, GitHub
  • Cleaned and preprocessed heterogeneous datasets using Pandas and NumPy to produce reliable model inputs for GenAI experiments.
  • Built baseline supervised models with Scikit-learn and evaluated them with precision and recall to guide iteration.
  • Prototyped Flask endpoints to serve model predictions for a web demo and validate end-to-end inference flow.
  • Visualized feature distributions and model diagnostics using Matplotlib to prioritize feature selection.
  • Managed code and dataset versions, and published reproducible notebooks and scripts to GitHub for review.
  • Synthesized analysis findings into concise reports for trainers to refine subsequent data collection and modeling steps.
InternCertify
Data Science Intern
Feb 2026 – May 2026
Three-month program covering end-to-end data analysis and model development workflows for real-world datasets.
Tech Stack: Pandas, NumPy, Scikit-learn, SQL
  • Processed and explored internship datasets using Pandas and NumPy to produce EDA summaries and visual insights.
  • Engineered features and applied statistical transformations to improve signal for predictive models.
  • Trained and tuned classification and regression models with Scikit-learn and assessed generalization with cross-validation.
  • Implemented SQL queries to extract, join and aggregate data for modeling inputs and feature generation.
  • Documented experiments and analysis pipelines in Jupyter notebooks, publishing reproducible artifacts to GitHub.
  • Prepared model evaluation reports that compared algorithms and informed selection of models for deployment.
AICTE (The Website Makers)
Data Analytics Intern
May 2025 – July 2025
Supported analytics and reporting for educational web platforms and internal stakeholders; built dashboards to accelerate reporting.
Tech Stack: Pandas, SQL, Power BI
  • Analyzed departmental performance datasets using Pandas to identify missing values and inconsistent KPIs prior to reporting.
  • Built interactive dashboards in Power BI to visualize enrollment and performance metrics for internal stakeholders.
  • Designed ETL steps and SQL transformations to consolidate data exports for consistent reporting inputs.
  • Implemented reusable Power BI measures and templates to accelerate report production across departments.
  • Validated reporting logic and implemented data quality checks to reduce downstream rework.
  • Streamlined report generation workflows, resulting in a 30% reduction in reporting time.
Refund Fraud Analytics

Projects

E-commerce Return & Refund Fraud Analytics | Dec 2025 – Apr 2026
Tools Used: Python, MySQL, Scikit-learn, Tableau, Flask
  • Built a fraud detection pipeline using Python to preprocess transaction and return logs and extract fraud-relevant features.
  • Implemented SQL queries in MySQL to join orders, returns and user tables for feature aggregation used by models.
  • Trained a Random Forest classifier to detect fraudulent return requests and analyzed feature importance to surface fraud patterns.
  • Created interactive Tableau dashboards to visualize flagged transactions, fraud trends and model confidence for investigators.
  • Deployed a Flask web application to expose real-time fraud prediction endpoints and enable demo-driven review workflows.
AI-Powered Customer Segmentation & Marketing Intelligence System | Apr 2024 – Aug 2024
Tools Used: Python, Pandas, Scikit-learn, Tableau
  • Developed clustering-based customer segmentation using feature-engineered behavioral and demographic attributes.
  • Performed EDA and feature scaling with Pandas to improve clustering separation and segment interpretability.
  • Evaluated segmentation via silhouette scores and refined features to improve actionable group differentiation.
  • Built Tableau dashboards to present segment profiles and campaign performance recommendations for targeted marketing.
Student Marks Prediction | Mar 2025 – Aug 2025
Tools Used: Python, Scikit-learn, Flask, Microsoft Excel, HTML, CSS
  • Developed a linear regression model in Scikit-learn to predict student marks from academic and attendance features.
  • Conducted feature engineering and EDA with Pandas to improve model inputs and reduce multicollinearity.
  • Deployed the model via a Flask application with a simple HTML/CSS frontend for real-time predictions.
  • Validated predictions and summarized results in Excel pivot tables to compare predicted vs actual performance.

Education

Sri Venkateswara College of Engineering & Technology
Bachelor of Technology (B.Tech) - Computer Science and Engineering • 2022 – 2026

Certifications

SQL • Feb 2026
Fundamentals of Data Analytics • Mar 2024
Programming for Data Analytics • Aug 2024
Analyzing Data with R • May 2024
Visualizing Data with R • May 2024
Data Science Foundations • Dec 2022

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