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Darga Shaik Mahammad Saifulla

Data Analyst Engineer | Java Developer • Proddatur, Andhra Pradesh, India • d*********@gmail.com • +91*******055 • linkedin.com/••••• • drivetube.ai/•••••

Professional Summary

Data Analyst Engineer with 0 years of experience in data analysis, ETL pipeline development, dashboard creation, and Java application development. Skilled in Python, SQL, Power BI, and Java; delivered stakeholder-ready dashboards and end-to-end data workflows and prototyped predictive models with strong focus on data quality and reproducibility.

Technical Skills

Programming Languages: Python,Java
Frameworks and Libraries: Pandas,NumPy,scikit-learn,Matplotlib
Databases: SQL,MySQL,JDBC,DBMS,SQL querying
Data and Analytics: ETL pipelines,Data cleaning,Feature engineering,Data preprocessing,Power BI,Tableau,Microsoft Excel,KPI reporting,Supervised learning,Model evaluation,SMOTE,Model prototyping
Tools and Methodologies: Git,GitHub,VS Code,IntelliJ IDEA
Analysis Methods & Concepts: Exploratory data analysis,Statistical analysis,Ad hoc analysis,Dashboarding

Work Experience

Academic & Self-Initiated
Proddatur / Remote
Data Analysis & Dashboard Development
2023 – 2025
Conducted end-to-end data analysis and dashboard development for academic datasets and self-initiated business problems; built repeatable ETL pipelines and stakeholder KPI reports.
Tech Stack: Python, Pandas, NumPy, scikit-learn, SQL, Power BI, Microsoft Excel, Git, GitHub
  • Performed end-to-end data cleaning and preprocessing using Python (Pandas) and SQL to standardize multiple datasets and improve downstream analysis reliability.
  • Designed and implemented ETL pipelines to automate ingestion, transformation, and loading of data for reporting workflows using Python scripts and SQL workflows.
  • Built interactive Power BI dashboards with drill-downs and KPI visuals to communicate trends and metrics to stakeholders, enabling faster insight discovery.
  • Conducted exploratory data analysis and statistical testing to identify patterns and anomalies that informed prioritization of business questions.
  • Engineered features and prototyped simple predictive models using scikit-learn to validate hypotheses and prioritize variables for production models.
  • Maintained version-controlled project repositories on GitHub and documented data dictionaries and transformation logic for reproducibility and handoff.
Pantech e-Learning
Remote
Java Developer Intern
Apr 2024 – Jun 2024
Remote internship focused on desktop application development and Core Java/JavaFX training; implemented OOP designs and handled structured datasets within Java applications.
Tech Stack: Java, JavaFX, Java Collections, OOP, Git, GitHub, IntelliJ IDEA, VS Code
  • Developed a full-featured desktop application using Java and JavaFX, applying OOP principles and MVC design to keep UI, business logic, and data access separable.
  • Implemented data handling and in-memory data structures using Java Collections Framework to manage large record sets efficiently and improve UI responsiveness.
  • Created JavaFX UI components and navigation flows, added input validation and comprehensive exception handling to improve user experience and stability.
  • Completed 3+ structured Core Java mini-projects demonstrating concepts such as collections, file I/O, and object-oriented design to reinforce production practices.
  • Used Git and GitHub for version control, participated in code reviews, and iterated on feedback to raise code quality and maintainability.
  • Documented application architecture and delivered a packaged application suitable for training demonstrations and internal evaluation.

Projects

ChurnShield – Telecom Customer Churn Prediction | Jul 2025 – Jul 2025
Tools Used: Python, Pandas, NumPy, scikit-learn, Matplotlib, SMOTE, Random Forest, Logistic Regression, XGBoost, ETL
  • Conducted exploratory data analysis and statistical analysis on 7,000+ telecom customer records to identify key churn drivers and data quality issues.
  • Built an ETL pipeline for data cleaning, encoding categorical variables, handling imbalanced classes with SMOTE, and preparing datasets for modeling.
  • Trained and compared Random Forest, Logistic Regression, and XGBoost classifiers; achieved 91% accuracy and 88% recall for the selected model and delivered a stakeholder-ready churn analysis report.
  • Segmented customers into churn-risk tiers and provided actionable retention recommendations that estimated a ~15% reduction in projected churn if targeted.
  • Documented modeling decisions, feature importances, and evaluation metrics to support future model iteration and handoff to engineering.
Student Management System – Desktop Application | Jul 2024 – Jul 2024
Tools Used: Java, JavaFX, MySQL, JDBC, MVC, OOP
  • Built a GUI-based CRUD application using Java and JavaFX to manage 500+ student records with MySQL integration via JDBC for persistent storage.
  • Applied MVC architecture, input validation, and error handling to create a scalable, maintainable application, reducing manual retrieval time by ~40%.
  • Implemented real-time synchronization between UI and database operations and documented the deployment steps for easy demo and evaluation.
  • Designed database schema and optimized queries to ensure responsive UI interactions for frequent record operations.
  • Packaged the application for distribution and created user documentation for installation and usage.

Education

Annamacharya Institute of Technology & Sciences, Rajampet
B.Tech – CSE (Data Science) • Rajampet, Andhra Pradesh, India • 2022 – 2026
Abhyas Junior College, Proddatur
Intermediate (MPC) • Proddatur, Andhra Pradesh, India • 2020 – 2022

Certifications

Advanced Data Science — APSSDC (IES) • Jul 2024
Industrial Internet of Things — NPTEL • Oct 2024
Java Programming — Pantech e-Learning • Apr 2025
Power BI Workshop — Industry Training • Apr 2023

Achievements

  • State-level Baseball Player — School Games Federation of Andhra Pradesh — Jan 2020: Represented at state-level competitions.
  • Active GitHub Contributor: Maintains data analysis and software engineering project repositories with reproducible notebooks and code.

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