Available for Opportunities

Sai Shiva

Technology , AI & Cybersecurity Enthusiast

Bridging the gap between human needs and digital solutions. Exploring Full Stack Development, Data Analytics, Cybersecurity, and Low-Code Platforms.

Resumé Explore Work

About Me

Who I Am

A versatile problem solver blending technical deep-dives with rapid deployment prototypes.

I'm Sai Shiva, a tech enthusiast with a holistic view of modern computing. My focus doesn't just rest on writing scalable code, but on understanding how data flows, how systems are defended, and how products can be deployed rapidly.

Whether I'm developing robust custom backends, analyzing datasets for actionable intelligence, fortifying networks securely, or leveraging low-code tools to solve business needs instantly—I approach every challenge with strategic execution.

4+ Domains
Explored

10+ Core
Technologies

2+ Professional
Specializations

Multidisciplinary Focus

Full Stack web development

Designing custom architectures while also leveraging platforms for rapid agile enterprise delivery.

Analytical & Secure

Data & Cyber

Harnessing data for decision-making and implementing security-first design principles inside applications.

B.Tech – Electronics & Communication Engineering

Building foundational academic knowledge in engineering alongside modern, self-taught practical skills.

Capability Matrix

Domain Expertise

Core tools and disciplines I rely on to execute complex projects.

Full Stack Dev

Data Analytics

Cybersecurity

Low/No-Code

SQL & Data Modeling

Azure & AI Tools

Portfolio

Featured Work

Demonstrating cross-functional capabilities through real-world applications.

Threat Intelligence Dashboard

Real-Time Cybersecurity Project
The Challenge: Security analysts frequently lose critical response time manually querying multiple, disparate threat intelligence platforms to investigate suspicious IP addresses, URLs, and newly disclosed vulnerabilities.
The Solution: I engineered a centralized, interactive threat intelligence platform designed to aggregate and visualize data from tier-one security feeds (AbuseIPDB, AlienVault OTX, URLhaus, NVD). Built with Python and Streamlit, the application features a robust SQLite backend that processes incoming telemetry and presents it through dynamic Plotly visualizations.

Python Security API

Library Management System

Designed and developed a scalable Library Management System using Java and Spring Boot to manage book inventory, user records, and borrowing operations. The system leverages a hybrid database architecture—using MySQL with Spring Data JPA for structured transactional data and MongoDB for flexible storage of book metadata. Implemented secure and well-structured RESTful APIs to enable seamless integration with front-end applications, ensuring efficient data handling and system performance.

Java Spring Boot MySQL MongoDB

Credit Card Default Risk Intelligence Platform

Designed and developed a data-driven Credit Risk Intelligence Platform using Python to analyze over 30,000 customer records. The system focuses on identifying key factors influencing default behavior through structured data processing, feature engineering, and exploratory analysis. Critical risk indicators such as payment delays and credit utilization were derived and analyzed to uncover high-risk customer segments. The project simulates real-world financial risk assessment by enabling data-driven insights that support better credit decision-making.

Python Pandas NumPy Matplotlib Seaborn

Customer Churn Analysis

Customer Churn Analysis is a data science project aimed at understanding why customers leave a service and predicting potential churn using machine learning models.

The project uses historical customer data to uncover behavioral patterns, perform exploratory analysis, and train predictive models that estimate churn risk.

Businesses often struggle to retain customers due to lack of predictive insights. This project helps organizations identify high-risk customers and take proactive measures to improve retention.

Data Analysis Machine Learning Python Data Visualization

E-Commerce Data Warehouse

Designed and built a scalable E-Commerce Data Warehouse using MySQL to transform raw transactional data into a structured analytics-ready system. Implemented a multi-stage ETL pipeline to process over 500,000 records, including data cleaning, transformation, and loading into a Star Schema with fact and dimension tables. Applied data quality checks, indexing, and optimized schema design to improve query performance and enable faster, reliable business reporting and insights.

MySQL ETL Data Modeling Star Schema

Employee Leave Management System

Designed and developed an Employee Leave Management System using Microsoft Power Apps to streamline leave requests, approvals, and employee record management. Built an intuitive interface for employees and managers to track leave balances, submit requests, and monitor approval workflows in real time. Integrated backend data storage and automated workflows to improve efficiency, reduce manual tracking, and ensure accurate leave management across the organization.

Power Apps Power Automate Dataverse SharePoint

Validation

Official Credentials

Industry-backed certifications solidifying foundational logic and system expertise.

Azure AI Fundamentals

Microsoft

Verified · 2025

Python for Datascience, AI & Development

IBM / Coursera