SHAIK NAYEEMAH GULFASHAN
Hyderabad
Summary
Seeking a Data Analyst skilled in SQL, Python, Excel, Power BI, and Tableau, eager to apply data cleaning, visualization, and forecasting skills to deliver business insights and to contribute to data driven decision making in a growth focused organization.
Overview
1
1
Certification
Work History
Data Analyst Intern
AI Variant
02.2024 - 08.2024
- Cleaned and transformed large e-commerce and HR datasets using Excel and SQL to ensure accuracy and consistency.
- Developed and deployed interactive dashboards in Tableau and Power BI showing trends in sales, customer behavior, delivery efficiency, employee attrition, and performance KPIs.
- Analyzed and identified critical business drivers including factors impacting sales, customer satisfaction, delivery delays, and workforce retention.
- Delivered and presented actionable insights with recommendations that supported process improvements and strategic HR and business decisions.
Education
Bachelor’s Degree - Information Technology
Vidya Jyothi institute of Technology
Hyderabad, Telangana12.2024
Skills
- Python Programming
- R Programming
- Tableau visualization
- SQL database management
- Power BI
- Excel
- Data Cleaning
- Analyzing
- Data visualization
- Dashboard development
- Business insights presentation
- Effective communication
- Teamwork and collaboration
- Problem-solving
Certification
- Data Analyst, ExcelR
- Python, Cisco
- Data Science & Math, Coursera
- Cloud Security, IEEE
- RPA, Blue Prism
- Internship, AI Variant
Accomplishments
Successfully cleared level 1 in MS word shortcut keys and is certified as a professional by RankSheet.
Languages
Hindi
First Language
English
Upper Intermediate (B2)
B2
Telugu
Elementary (A2)
A2
Academic Projects
Stock Analysis using Time Forecasting Methods
Tools: Google Colab, Python, Keras, Matplotlib, Pandas, NumPy
- Developed a model using RNN and LSTM to predict Google stock prices from 2012 to 2017
- Trained models with multiple epochs, achieved the best accuracy in forecasting with LSTM at 50 epochs being optimal
- Visualized predicted vs. actual values using candlestick charts and comparative plots
IPL prediction using machine learning
Tools: Python, Pandas, NumPy, Matplotlib, Flask, Jupyter Notebook
- Collected and cleaned IPL match data including player stats, team rankings, and pitch/weather conditions.
- Built predictive model using Lasso Regression with feature selection, achieving 75% accuracy.
- Deployed Flask web application for real-time match prediction.
Timeline
Data Analyst Intern
AI Variant
02.2024 - 08.2024
Bachelor’s Degree - Information Technology
Vidya Jyothi institute of Technology
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