I am a recent M.S. graduate in Artificial Intelligence and Business Analytics from the University of South Florida, with a 4.0/4.0 GPA and 4+ years of combined experience across data analytics, ETL workflows, SQL, cloud platforms, dashboarding, automation, and machine learning applications.
My portfolio brings together data engineering, analytics engineering, data science, machine learning, deep learning, real-time streaming, big data, BI dashboards, RAG systems, and AI agents. I enjoy building practical systems that move from raw data to reliable insights, predictive models, and decision-ready applications.
Currently focused on: Data Science • Data Engineering • AI/ML Engineering • Analytics Engineering • Business Intelligence
- Build end-to-end data pipelines using Python, SQL, Airflow, Spark, Kafka, and cloud services
- Design analytics-ready databases and warehouses using PostgreSQL, MySQL, MongoDB, Cassandra, and CockroachDB
- Develop machine learning models for forecasting, classification, NLP, anomaly detection, and computer vision
- Create BI dashboards and analytical reports using Power BI, Tableau, Excel, and SQL
- Build GenAI and RAG applications using FastAPI, React, LangChain, LangGraph, embeddings, and vector databases
- Translate technical results into business insights, recommendations, and measurable impact
| Area | Summary |
|---|---|
| Data & Analytics | Experience working with SQL analytics, ETL workflows, dashboards, reporting, and data validation |
| Cloud & Automation | Hands-on exposure to cloud-based data workflows, orchestration, automation, and monitoring concepts |
| Graduate Assistantship | Supported analytics instruction, Excel/R-based statistical analysis, dashboard evaluation, grading, and student project guidance |
| Machine Learning | Built academic and portfolio projects across forecasting, NLP, anomaly detection, computer vision, risk prediction, and classification |
| Communication | Experienced in explaining analytical results, documenting workflows, and translating data findings into practical recommendations |
End-to-end Formula 1 analytics and race prediction platform using PostgreSQL, dbt, XGBoost, Airflow, Docker, and BI dashboards.
Python SQL PostgreSQL dbt Airflow XGBoost Docker BI
Real-time streaming pipeline using Kafka, Spark Structured Streaming, MongoDB, Docker, and Python to process IoT air-quality data and generate low-latency alerts.
Kafka Spark Structured Streaming MongoDB Python Docker Big Data
Production-style analytics warehouse using Python ETL, PostgreSQL, star schema modeling, SQL analytics, and Tableau dashboards.
Python PostgreSQL ETL Data Warehouse Star Schema Tableau
Applied AI system combining Temporal Fusion Transformer forecasting and PPO reinforcement learning for demand prediction and pricing optimization.
PyTorch Time-Series Forecasting TFT PPO Reinforcement Learning
Full-stack document intelligence platform using FastAPI, React, vector search, embeddings, and RAG for semantic document Q&A.
FastAPI React RAG Vector Search Embeddings Semantic Search
PostgreSQL optimization project using indexing, partitioning, EXPLAIN ANALYZE, Docker, and SQL tuning, achieving up to 96% query performance improvement.
PostgreSQL SQL Optimization Indexing Partitioning Docker
| Project | What It Demonstrates | Stack |
|---|---|---|
| formula1-predictive-analytics-platform | Predictive analytics pipeline and BI workflow | PostgreSQL, dbt, XGBoost, Airflow, Docker |
| real-time-iot-air-quality-pipeline | Real-time streaming and IoT analytics | Kafka, Spark, MongoDB, Docker |
| movielens-data-warehouse | Data warehousing and dimensional modeling | Python, PostgreSQL, SQL, Tableau |
| streamflix-db-performance-optimization | SQL tuning and database optimization | PostgreSQL, Indexing, Partitioning, Docker |
| hadoop-ecommerce-analytics | Distributed batch analytics | Hadoop, HDFS, YARN, MRJob, Python |
| fleet-telemetry-mongodb-platform | NoSQL IoT data modeling | MongoDB, Aggregation, Indexing |
| fleet-telemetry-cassandra-platform | Distributed NoSQL design | Cassandra, CQL, Docker |
| multi-region-fleet-iot-database-architecture | Multi-region distributed database architecture | CockroachDB, Docker, Python, SQL |
| Project | What It Demonstrates | Stack |
|---|---|---|
| ai-retail-demand-forecasting-dynamic-pricing | Forecasting and decision optimization | TFT, PPO, PyTorch |
| ecg-anomaly-detection-vae | Unsupervised anomaly detection | VAE, PyTorch, ROC-AUC, t-SNE |
| sign-language-recognition-cnn | Computer vision classification | CNN, PyTorch |
| fake-news-detection-ml | NLP text classification | TF-IDF, SVM, Logistic Regression |
| obesity-classification-ml | Traditional ML classification | SVM, Decision Tree, Random Forest |
| advertising-campaign-analysis | A/B testing and regression analysis | R, Statistics, Regression |
| mental-health-risk-prediction-system | ML risk-screening API workflow | XGBoost, Flask, Docker, Scikit-learn |
| ai-generated-text-detection-system | NLP-based AI text detection | BERT Embeddings, Streamlit, Similarity Scoring |
| Project | What It Demonstrates | Stack |
|---|---|---|
| rag-document-intelligence-platform | Document intelligence and RAG | FastAPI, React, Vector Search |
| agentic-research-workflow-platform | Multi-agent research orchestration | LangGraph, FastAPI, React, Ollama |
| context-aware-browser-assistant | Privacy-first browser AI assistant | React, TypeScript, Chrome Extension, Ollama |
| multimodal-audio-generation-platform | Text-to-audio generation optimization | AudioLDM, CLAP, PyTorch |
| autonomous-ai-code-repair-platform | AI-powered code repair and validation | LangGraph, Docker, GitHub API, pytest |
| Project | What It Demonstrates | Stack |
|---|---|---|
| air-pollution-life-expectancy-analysis | Public-health analytics and storytelling | Tableau, EDA, Global Health Data |
| advertising-campaign-analysis | Marketing analytics and experimentation | R, A/B Testing, Regression |
| movielens-data-warehouse | BI dashboarding on warehouse data | Tableau, SQL, PostgreSQL |
- M.S. in Artificial Intelligence and Business Analytics — University of South Florida, May 2026 | GPA: 4.0/4.0
- Graduate Assistant experience, University of South Florida — implemented analytics evaluation workflows across statistical analysis, dashboard review, business decision modeling, grading operations, and project quality assessment
- 4 years of combined systems engineering, analytics, and data-oriented workflow experience, including exposure to ETL processes, SQL analytics, cloud data platforms, automation, reporting, and stakeholder collaboration
- Email: sucharitha1812@gmail.com
- LinkedIn: linkedin.com/in/sucharitha-gaddam
- GitHub: github.com/sucharitha1812
- Location: Tampa, FL
As a recent May 2026 graduate, I am actively exploring opportunities in:
Data Analyst Business Intelligence Analyst Data Scientist Data Engineer Analytics Engineer AI Engineer Machine Learning Engineer Cloud Data Engineer