Results-driven Data Analyst with 5+ years of experience in data analytics, automation, and business intelligence across healthcare, tech, and compliance sectors. Expert in transforming complex datasets into strategic insights using SQL, Python, and AI/ML. Proven track record in reducing manual efforts, improving system performance, and delivering executive-ready dashboards.
Python – PySpark, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch
SQL – Advanced querying, ETL, data validation, Stored Procedures
Other Languages – SQL, JAVA, C++
LLMs & Frameworks: Google Gemini, LangChain, Transformers, HuggingFace
Techniques: Retrieval-Augmented Generation (RAG), Prompt Engineering, Text Classification, Sentiment Analysis
Core NLP: NLTK, spaCy, Text Preprocessing
Core ML: Time-Series Forecasting (ARIMA, Prophet), Anomaly Detection, Recommendation Systems, Statistical Modeling, A/B Testing
Deep Learning: Computer Vision (OpenCV), Graph Neural Networks (GNNs)
Platforms: AWS SageMaker, GCP Vertex AI, Databricks
Orchestration & Pipelines: Airflow, CI/CD, ETL Pipelines
Infrastructure: Docker, Kubernetes, Confluent Kafka
Data Storage: Data Warehousing (Redshift, Snowflake), Data Modeling
Deployment: FastAPI, Streamlit
Databases: PostgreSQL, MySQL, SQL Server, Neo4j (Graph), MongoDB
Visualization: Tableau, Power BI, QlikSense, Cognos, MicroStrategy
Collaboration & Workflow: Git, GitHub, Jira, Confluence, Agile/Scrum
Here are a few projects that reflect my skills and problem-solving capabilities:
AI agent that tailors resumes, matches job descriptions, and writes personalized cover letters.
- Tools: Python, Google Gemini Pro, Prompt Engineering
- Outputs: Match scoring, bullet suggestions, JSON-structured output
- Featured on Kaggle, GitHub, and YouTube
🔗 GitHub Repo | Kaggle Notebook | YouTube Demo
Leverages LLMs and AI agents to automatically analyze reports (PDF/Excel/CSV) and generate actionable summaries, charts, and insights.
🔍 Automated insight extraction using Python & OpenAI APIs
📊 Visualizations using Plotly and Matplotlib
🤖 Intelligent summarization & natural language generation
An interactive Streamlit application visualizing and comparing cost of living indices across various countries.
Technologies Used: Python, Streamlit, Pandas, Plotly, Seaborn
Features:
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🗺️ Compare indices by country using visual charts
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📊 Built with Plotly, Seaborn, Streamlit
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🧮 Focus on rent, groceries, utilities, etc.
Outcome: Facilitates users in making informed decisions regarding global cost comparisons.
Analyzes sales data and builds time-series models to forecast future trends.
- 🧼 Data wrangling and preprocessing with Pandas
- 📈 Time-series forecasting with ARIMA & statsmodels
- 📉 Actionable sales insights for business planning
📬 Let’s Connect
I’m always excited to collaborate, learn, or just chat about data!
📧 Email: [email protected]
🧠 Portfolio Website: https://sreejabethu.github.io/datascience/
📍 Location: United States (Open to Remote & Hybrid Roles)
Let’s make data work smarter with AI 🚀