🎓 MS in Information Technology & Analytics @ RIT, USA
📊 Building analytics, ML models, dashboards & NLP solutions
💼 Actively seeking Full-Time roles (Data Analyst | BI Analyst | Data Scientist)

I am a Data Analytics & BI professional who loves transforming raw data into meaningful, actionable insights.
With experience across Power BI, Python, SQL, NLP, Machine Learning, and Time Series Forecasting,
I build end-to-end analytical solutions that solve business problems.

Previously, I worked as a Frontend Developer & Chatbot Developer (TCS),
and now I blend my technical + analytical skills to deliver powerful data-driven solutions.

Languages:
Python • SQL • R • JavaScript • HTML/CSS

Data Science & ML:
Pandas • NumPy • Scikit-learn • SARIMA • XGBoost • Prophet • LSTM • NLP (spaCy, BERT, TF-IDF)

Business Intelligence:
Power BI • Tableau • Looker Studio • DAX • ETL Pipelines

Databases:
MySQL • MongoDB

Other:
Git/GitHub • API Integration • Time-Series Forecasting • Data Modeling • Microsoft Azure

Power BI dashboard analyzing revenue, ROAS, ROI, funnel performance, and customer segmentation.
Tools: Power BI, SQL, DAX, Star Schema
🔗 Repo: https://github.com/jueeli97/Ecommerce_Marketing_Analytics

NLP + IR project analyzing topics, sentiment, co-occurrence, TF-IDF & inverted/positional indexes on podcast transcripts.
Tools: Python, spaCy, BERT, NetworkX
🔗 Repo: https://github.com/jueeli97/TextMiningAndAnalysis

Classified real vs fraudulent job posts using NLP, TF-IDF, Random Forest, Logistic Regression.
Tools: Python, Scikit-learn
🔗 Repo: https://github.com/jueeli97/DSCI-633/tree/main/assignments/project

Cross-country analysis exploring how corruption influences trust, governance quality, health coverage, and socio-economic indicators using statistical modeling and interactive dashboards.
Tools: R, tidyverse, ggplot2, corrplot, Tableau, data visualization
🔗 Repo: https://github.com/jueeli97/Corruption-Analysis

End-to-end Python pipeline using SARIMA, Prophet, XGBoost & LSTM with engineered weather/seasonal features to forecast New York’s electricity consumption.
Tools: Python, ML, Time Series, Power BI
🔗 Repo: https://github.com/jueeli97/Capstone_Electricity_Forecasting

Interactive healthcare analytics dashboard that analyzes 30-day hospital readmissions using real-world patient encounter data.
Tools: R, Shiny, shinydashboard, dplyr, ggplot2, caret, pROC
🔗 Repo: https://github.com/jueeli97/Hospital-Readmission-Analytics

• LinkedIn: https://www.linkedin.com/in/jueeli-sawant-8697441b6/
• GitHub: https://github.com/jueeli97
• Email: jueeli97@gmail.com