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:

• 🗺️ Compare indices by country using visual charts

• 📊 Built with Plotly, Seaborn, Streamlit

• 🧮 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

View on Kaggle Kaggle Profile Kaggle Competitions Kaggle Datasets Kaggle Notebooks Kaggle Discussions

📬 Let’s Connect

I’m always excited to collaborate, learn, or just chat about data!

🔗 LinkedIn

📧 Email: bethusreeja@gmail.com

🧠 Portfolio Website: https://sreejabethu.github.io/datascience/

📍 Location: United States (Open to Remote & Hybrid Roles)

Let’s make data work smarter with AI 🚀