SAI SIDDARTHA M

Data Analyst
Bangalore, IN.

About

Highly skilled Data Analyst with a proven track record in SQL, Python, Excel, and Power BI, adept at transforming complex datasets into actionable insights and automated dashboards. Expertly applies advanced analytics to identify trends and optimize operations across retail and e-commerce, with a keen interest in supply chain and warehouse efficiencies. Leverages strong proficiency in KPI tracking, data modeling, and decision support systems to drive significant business impact and improve decision-making.

Education

New Horizon College of Engineering
Bangalore, Karnataka, India

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B.Tech.

Information Science and Engineering

Grade: 7.0/10 CGPA

Certificates

Data Analyst Bootcamp

Issued By

Alex the Analyst

Excel Workshop

Issued By

Newton School

Skills

Business Intelligence & Visualization

Advanced Excel, Pivot Tables, Power Query, Lookups, Power BI, DAX, Data Modelling, KPI Tracking.

Programming & Data Analysis

Python, NumPy, Pandas, Matplotlib, Seaborn, Data Visualization, EDA, Data Wrangling.

Databases

MySQL, PostgreSQL.

Professional Skills

Issue Resolution, Root Cause Analysis, Cross-functional Collaboration, Insight Presentation.

Operational Analytics

Warehouse Management Systems (WMS), Inventory Analytics, Order Fulfillment KPIs.

Projects

Coffee Shop Dashboard

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Summary

Developed an interactive MS Excel dashboard to analyze coffee shop sales data, providing key insights into sales performance, customer loyalty, and operational efficiencies for strategic decision-making.

New York Airbnb Project

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Summary

Analyzed Airbnb listing data using Python, Pandas, Seaborn, and Matplotlib to uncover key revenue drivers, pricing impacts, and seasonal booking trends, providing strategic insights for hospitality and warehouse operations.

Costco Sales Data Analysis

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Summary

Transformed multi-table Excel data into a robust relational model using Power BI and DAX, enhancing sales strategy and operational efficiency through dynamic trend analysis and customer retention insights.

Amazon Data Analysis

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Summary

Performed comprehensive SQL-based analysis on 21.6k+ rows of Amazon transaction data to improve data reliability, understand customer churn patterns, and identify seasonal sales trends for inventory planning.