Shreetej Khawate

Results-driven and detail-oriented MCA graduate with a strong foundation in data analysis, SQL, Excel, Power BI, and Tableau. Passionate about deriving insights from data to drive business decisions. Seeking an entry-level Data Analyst role to leverage analytical skills, and technical expertise.

.Data Analytics with Python, 5 Minutes Engineering

. IABAC certification in Data Science

Member of Data Science Club at Modern College of Engineering Participated in hackathons and data analysis competitions Contributed to open-source data projects on GitHub

Worked with Radio Mirchi for Kumar Sanu live-in Concert.
* Worked with “YUVAK BIRADARI” for Ek sur Ek taal event.
* Worked as a intern with Radio Mirchi for their event “THUNDER RUN”. • Volunteered at National Teacher’s Congress at
MIT-WPU.
* Worked at Lokmat. • Volunteered at Bhartiya Chattra Sansad in MIT-WPU. • And many more events I volunteered in MIT
WPU College As well as outside of the College.
* Worked for Diljit Dosanjh concert,AMANORA MALL PUNE .

1)Confirm Tickett – Railway Ticket Confirmation Prediction System

Developed a machine learning-powered web application to predict railway ticket confirmation probability based on user inputs like train type, quota, waiting list number, and passenger details. The model, built using Scikit-learn, Pandas, and NumPy, provides real-time probability predictions. The application is deployed using Streamlit with a backend database in SQLite to store user inputs and predictions for analysis.

Key features include strict input validation, data logging, CSV export for reports, and real-time probability visualization. The model is continuously improved by incorporating real-time user data, enhancing prediction accuracy and reliability.

2)Sales Data Analysis using SQL & Power BI

 Extracted, cleaned, and analyzed sales data from a database., Created interactive dashboards in Power BI to visualize trends., Provided business insights for revenue growth. Customer segmentation using Python, performed clustering analysis on customer data using Python, used K-means algorithm to segment customers based on purchasing behavior, and recommended targeted marketing strategies for different segments

3) Flight Fare Prediction Model

 Used machine learning to estimate ticket prices based on factors like airline, date, duration, and stops.It involves data preprocessing, feature engineering, and model selection (Linear Regression, Random Forest, or XGBoost). The model helps travelers and airlines optimize pricing strategies and predict future fare trends accurately

• English (Fluent)
• Hindi (Fluent)
• Marathi (Fluent)

Data Science Consultant, Rubixe Ai Company, Bangalore, 01/25, 02/25, Assisted in analyzing company data to identify key trends., Wrote SQL queries to extract data and generate reports., Developed dashboards using Power BI for business presentations.