Nibedita Sahu

|

About Me

Hi, I’m Nate (short for Nibedita), a Data Science & Analytics Enthusiast with a strong foundation in Mathematics. I specialize in using Python, SQL, Power BI, and Business Mathematics & Statistics to analyze, visualize, and interpret data. With a passion for Problem-Solving and Data Storytelling, I focus on making complex data easy to understand through clear insights and visualizations. I'm constantly learning and refining my existing skills, working on projects that challenge me to grow and explore new opportunities.



View Resume

Skills

Tools & Technologies

Programming Languages: Python SQL

Libraries: NumPy Pandas Matplotlib Seaborn

Version Control: Git GitHub

Development Environments: VS Code Jupyter Notebook Google Colab

Data Management & Reporting: Power BI Excel

Reporting & Designing: PowerPoint Canva

Techniques & Concepts
Data Gathering Data Cleaning Data Preprocessing Data Integration Exploratory Data Analysis (EDA) Business Mathematics Statistical Analysis Predictive Analytics Machine Learning Basics Feature Engineering Time Series Analysis Data Visualization Reporting & Dashboarding Data Storytelling Business Understanding Analytical Thinking Problem Solving Decision Making

Background

šŸŽ“ Bachelor of Science in Mathematics

With a strong analytical mindset shaped through my academic journey, I've developed a natural inclination toward solving data-driven problems. My degree has helped me understand the logic, structure, and patterns that form the backbone of Data Science & Analytics.


Kalahandi University, Bhawanipatna, Odisha
2020-2023

Projects

Project 5 Image

Electric Vehicle Population Analysis

A complete end-to-end data analysis project exploring Electric Vehicle adoption. Used SQL, Python, and Power BI to clean, analyze, and visualize trends in EV types, range, and policy eligibility. Delivered actionable insights on top-performing models, regional adoption, and CAFV alignment through a multi-page report and presentation.

GitHub

IBM HR Employee Attrition Analysis

This project analyzes employee turnover using Python and Power BI to find out why employees leave. It explores factors like job roles, departments, and employee demographics to identify patterns and trends. The insights help HR teams make better decisions to improve employee retention. Visualizations and data-driven analysis make it easy to understand key factors affecting attrition.

GitHub View Notebook
Project 4 Image
Project 3 Image

Customer Sales Performance Analysis

An end-to-end data analytics project analyzing customer sales using Python, SQL, and Power BI. Data was explored and cleaned in Jupyter Notebook, queried with MySQL, and visualized through interactive Power BI dashboards to enable clear identification of sales trends, customer behaviors, and key business drivers.

GitHub View Presentation

Credit Card Financial Analysis

A Power BI dashboard providing real-time insights into credit card transactions, customer behavior, and key financial metrics. The project leverages data visualization to identify spending patterns, detect anomalies, and support strategic financial decisions. It combines analytical rigor with intuitive design for effective data storytelling.

GitHub View Presentation
Project 2 Image
Project 1 Image

Super Store Sales Analysis & Forecasting

An interactive Power BI dashboard designed to analyze superstore sales data, track key performance indicators, and uncover actionable business insights. Leveraging time series analysis, the project provides accurate 15-day sales forecasts to support proactive decision-making. Explore sales trends, product performance, and regional patterns through intuitive visualizations and advanced analytics.

GitHub View Presentation
View More Projects

Try This Fun Program - Body Fat Calculator

This web app calculates Body Fat %, Fat Mass (kg), and Lean Mass (kg) interactively using the U.S. Navy formula. Built with Pandas & Streamlit.

GitHub Open Live App Read Article

Contact Me