Ramanand Pandey

Ramanand Pandey

Data Analyst
India
English, Hindi
Full-time On-site

نبذة عني

Data Analyst with 1+ year of hands-on experience analyzing sales, ERP, and market data using Excel, SQL, Python, and Power BI. Skilled in data validation, MIS reporting, exploratory data analysis, dashboard development, …

الخبرة

Data Analytics – GET

Prakash Pump EST · Ahmedabad
Jul 2025 - حتى الآن · 1 سنة 4 أشهر

<p>Analyzed and validated sales, dispatch, and ERP data in Excel using Pivot Tables and LOOKUP functions.</p><p> Identified and flagged a grand-total formula error in a dispatch MIS report during reporting validation.</p><p> Analyzed dewatering and sewage pump markets across multiple countries.</p><p> Compared competitor and market findings.</p><p> Presented management-ready insights to support business decisions.</p>

Data Science Intern

Celebal Technology · Jaipur
May 2024 - Aug 2024 · 3 أشهر

<p>Prepared analysis-ready data by cleaning and preprocessing unstructured datasets with Pandas and NumPy for downstream modeling.</p><p> Applied and compared K-Means and DBSCAN clustering in Scikit-learn to examine cluster patterns across prepared datasets.</p><p> Documented preprocessing, modeling steps, and analytical outputs in Jupyter Notebook to support reproducible analysis.</p>

المشاريع

Netflix Content Analytics (Python & SQL):

Prakash · https://github.com/RamanandPandey/netflix-content-analytics
المدة : 15-Jul-2025 - 20-Jan-2026

<p>Queried and analyzed content-addition trends using Python and SQL joins, CTEs, and window functions; annual additions rose from 82 titles in 2015 to 1,879 in 2020, with 2019 peaking at 2,016 titles. </p>

الشهادات

RHCSA EX-200

redhat · Jaipur , Rajasthan , India · 2025

المهارات

SQL Joins CTEs Window Functions Excel Pivot Tables LOOKUP Data Cleaning EDA Power BI DAX Dashboard Development KPI Reporting Data Visualization Python Pandas NumPy Matplotlib Seaborn Correlation IQR MIS Reporting Market Research Competitor Analysis Data Storytelling MySQL Jupyter Notebook Git GitHub Scikit-learn
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