Kusuma Satya Sreeja Photo

Portfolio · Data & AI

Kusuma Satya Sreeja Chalasani

Data Engineer · AI Systems Builder · Cloud (Azure & GCP)

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01 About Me

I’m Kusuma Satya Sreeja Chalasani — a Data Science graduate student passionate about building intelligent, real-world data solutions at the intersection of data engineering, machine learning, and AI-driven automation.

With hands-on experience in Python, SQL, GCP, and Azure, I design scalable data pipelines, develop anomaly detection systems, and build AI-powered workflows that automate decision-making. My work focuses on creating efficient, explainable, and production-ready systems that deliver meaningful impact.

Beyond technology, I’m an artist at heart. Whether I’m visualizing complex data or sketching creative ideas, I enjoy transforming concepts into clear and expressive forms. I believe the best data solutions combine analytical thinking with creativity — and that philosophy guides everything I build.

Currently, I’m exploring agentic AI systems and end-to-end data products that integrate data processing, modeling, and user-facing insights. I’m always excited to work on projects that blend data, AI, and design to solve real-world problems.

02 Education

Master of Science in Data Science

University of North Texas (UNT) 2024 – Present
  • Relevant Coursework: Machine Learning, Big Data, Data Engineering, Artificial Intelligence
  • Focus Areas: AI Agents, Data Pipelines, Cloud Computing
  • Currently building projects in AI-driven automation, anomaly detection, and intelligent systems

03 Skills

Core stacks at a glance—full write-ups live under Projects and Certifications.

Programming & Data Analysis

Python, SQL, Pandas, NumPy, OpenRefine, EDA & feature prep.

Used in: Interview Prep RAG, AI Data Analyst, Crime Rate Prediction, Guardian Recruit

Data Visualization

Matplotlib, Seaborn, Plotly, Recharts, Tableau, dashboards & time series.

Used in: LUMA 2.0, AI Data Analyst

Machine Learning, NLP & Explainable AI

Scikit-learn, BERT/SBERT embeddings, Isolation Forest, XGBoost, hybrid ensemble modeling, SHAP explainability, classification & clustering, ARIMA & LSTM.

Used in: Smart Job Matcher, Emotion-Based Music, Energy Forecasting, Guardian Recruit

Generative AI, RAG & Agents

LangChain, LangGraph, ChromaDB, Groq & Gemini, OpenAI GPT, Streamlit, prompts & context design.

Used in: Interview Prep RAG, LUMA 2.0, DishGenie

Cloud & Automation

Azure VMs & storage, GCP BigQuery & Dataproc, Splunk, PowerShell automation.

Used in: Crime Rate Prediction, DishGenie

Big Data & Streaming

PySpark, Hive, Spark Structured Streaming, ETL at scale.

Used in: Crime Rate Prediction

Modern Web & APIs

React, TypeScript, Tailwind CSS, Framer Motion, Flask, FastAPI, REST, HTML/CSS, JavaScript, responsive UI.

Used in: LUMA 2.0, Smart Job Matcher, AI Data Analyst

Tools & Delivery

Jupyter, Colab, VS Code, GitHub, Streamlit, Render, PostgreSQL, Excel, Google Sheets.

Used in: LUMA 2.0, Interview Prep RAG, DishGenie, Guardian Recruit

04 Experience

Professional Experience

Cloud Support Engineer - Data Engineering & Operations

DHL Project, Cloud4C | Jun 2022 – Jul 2024

  • Worked on enterprise cloud operations and data-driven systems for large-scale environments (DHL project), contributing across data engineering, analytics, and cloud infrastructure workflows.
  • Designed and supported data pipelines for extracting, transforming, and analyzing cloud usage and performance data using Python and SQL.
  • Processed and managed large-scale operational datasets, enabling analytics, reporting, and optimization initiatives.
  • Automated data extraction, transformation, and reporting workflows using Python and PowerShell, improving efficiency and reliability.
  • Performed trend analysis on cloud storage, logs, and performance metrics to support infrastructure planning and decision-making.
  • Worked with cloud platforms (Azure & GCP) to manage data workflows, storage systems, and processing pipelines.
  • Supported AI/analytics use cases by preparing clean, structured datasets for downstream modeling and insights.
  • Collaborated with cross-functional teams to ensure data availability, consistency, and system reliability across cloud environments.
  • Contributed to monitoring, troubleshooting, and optimization of cloud-hosted systems and data pipelines.
UNT Logo

Cross-Functional IT Support Specialist

University of North Texas - College of Merchandising, Hospitality & Tourism | Dec 2024 - Present

  • Provided cross-functional IT support to CMHT faculty, staff, and students for hardware, software, and system-related issues.
  • Troubleshot Windows OS, application, peripheral, network access, and user account problems.
  • Managed and supported 240+ student loaner laptops to keep devices secure, functional, and up to date.
  • Re-imaged, configured, and deployed end-user devices with required software and system configurations.
  • Assisted with patch management and update cycles to maintain stability and security compliance.
  • Supported front desk and checkout operations by handling technical inquiries and issue documentation.
  • Collaborated with IT teams and department staff to minimize downtime and improve day-to-day operations.

Academic & Project Experience

Guardian Recruit - AI-Powered Fraud Detection System

Duration | Jan 2026 - May 2026

  • Built a production-ready AI system to detect fraudulent job postings using a hybrid multi-model pipeline combining NLP, anomaly detection, and ensemble learning.
  • Designed an explainable AI framework using SHAP to provide transparent fraud probability insights and improve decision trust.

Deep Learning Interview Prep Agent (RAG System)

Duration | March 2026 - April 2026

  • Built an end-to-end Retrieval-Augmented Generation (RAG) system enabling document-based question answering with source-backed responses.
  • Implemented chunking, embeddings, and vector-based retrieval using ChromaDB, along with an interactive Streamlit UI.

Real-Time Crime Data Streaming (GCP)

Duration | 2025

  • Developed a real-time data pipeline using PySpark Structured Streaming on GCP Dataproc to process and analyze crime data.
  • Enabled continuous ingestion, aggregation, and visualization of key insights such as top crime types.

05 Projects

Interview prep RAG workspace with document viewer and grounded chat responses

Deep Learning RAG Interview Prep Agent

RAG-powered interview prep with grounded Q&A from your study materials.

Python LangChain LangGraph ChromaDB Streamlit Groq API
Live Demo
AI + ML
Guardian Recruit threat indicators dashboard with fraud detection signals and action panel

Guardian Recruit - Fraud Detection System

Production-ready AI system with explainable AI for fake job posting fraud detection.

Python NLP Machine Learning Explainable AI Streamlit XGBoost
Live Demo
AI + ML
DataPilot analytics workspace: dashboard, export results, and data overview

AI Data Analyst Agent

Automates analysis, charts, and ML to surface insights from tabular data.

React FastAPI Python Scikit-learn Plotly LLMs
Live Demo
Dishgenie Logo

DishGenie – AI Recipe Generator

Personalized recipes from ingredients and preferences using OpenAI GPT.

Flask JavaScript OpenAI API HTML/CSS Render
Live Demo
AI Automation
Internal hiring AI landing page preview with talent matching system metrics

Smart Internal Job Matcher & Email Notifier with AI

Semantic matching to roles with SBERT embeddings and automated email workflows.

Python FastAPI PostgreSQL SBERT React
Live Demo
Crime Analytics

Crime Rate Prediction – GCP Project

Cloud analytics pipeline for crime trend forecasting and visualization at scale.

BigQuery PySpark Hive Dataproc Python
Emotion + Music

Emotion-Based Music Recommendation System

Detects mood from faces and recommends music in real time via Spotify.

Python CNN OpenCV Spotify API
Energy Forecasting

Energy Consumption Forecasting

Time-series models to forecast household electricity usage with clarity.

Python ARIMA LSTM Matplotlib Seaborn

06 Certifications

Industry-recognized credentials across AI systems, cloud platforms, and production-ready agent development.

07 My Creative Space

Outside of my professional work in data science, cloud engineering, and AI, I explore creativity through pencil sketching and digital illustration.

This gallery features a few of my favorite works — blending emotion, culture, and character through art.

Pencil Sketch of Actor Lion King Fanart Little Krishna

Explore more of my work on Instagram:

@pencilart_love

08 Get in Touch

Actively seeking Data Engineering, AI, and Cloud opportunities. Let’s build scalable, real-world systems together.

🟢 Available for Internships & Full-Time Roles

📍 Texas, USA · Open to Remote & Relocation

Email LinkedIn GitHub

Usually responds within 24 hours