Chetan.
👋 Hello, Chetan here!

I turn data
into decisions.

I'm a Data Analyst 📊

Data Science graduate from Rutgers (4.0 GPA) with hands-on experience in operations analytics, Power BI dashboard development, and data modeling. I analyze operational datasets, build KPI-driven reporting, and help teams make data-driven decisions, from messy data to dashboards people actually use.

View My Projects → Resume ↓
$45M+
Sales data analyzed in Power BI
180+
Countries in food-security panel
58
CA counties in geospatial analysis
4.0
GPA · MS Data Science, Rutgers

I'm Chetan Injavarapu, a Data Analyst with a Master's in Data Science from Rutgers University (4.0 GPA). My work sits at the intersection of operations analytics, Power BI dashboard development, and data modeling. I turn messy operational datasets into KPI-driven reporting that people actually use to make decisions.

Before grad school, I earned a B.Tech in Computer Science and interned as a Data Science Intern, building ML models and analytical solutions with Python and SQL. At Rutgers, I managed building operations for Housing & Residence Life. I tracked service requests, improved response workflows, and kept operational records clean. That operations experience is exactly what makes my analytics practical: I've been the person relying on the data, not just building the dashboard.

My projects range from a Power BI solution analyzing $45M+ in retail sales to geospatial analyses spanning 180+ countries and 58 California counties. I care about data validation, reporting standards, and governance. That unglamorous work is what makes analysis trustworthy.

I'm currently seeking Data Analyst roles where analysis and visualization support informed, data-driven decision-making. ✨

profile
NAMECHETAN_INJAVARAPU
ROLEDATA_ANALYST
LOCATIONChandler, AZ OPEN TO RELOCATE
EMAILinjavarapuchetan@gmail.com
LINKEDIN@chetaninjavarapu
GITHUB@chetan-957
STATUSOPEN TO WORK
Background

Experience

Sep 2024 – Dec 2025

Building Manager (Operations)

Housing & Residence Life, Rutgers University — Camden, NJ
  • Managed day-to-day building operations supporting resident services, facility coordination, and operational workflows.
  • Tracked and monitored service requests, identifying recurring operational issues and improving response workflows.
  • Maintained accurate operational records ensuring data integrity for housing assignments, incidents, and service logs.
May 2022 – Jul 2022

Data Science Intern

ACME GRADE — India
  • Developed machine learning models and analytical solutions to support business decision-making.
  • Performed data analysis using Python and SQL to extract actionable insights from structured datasets.
  • Tracked KPIs and communicated results through visualizations and reports.
Education

Where I studied

Jan 2024 – Dec 2025 · Camden, NJ

Master's in Data Science

Rutgers University
GPA 4.0
2019 – 2023 · India

B.Tech in Computer Science

GITAM University
GPA 7.93
My Projects

What I've Built

A few projects I'm proud of — from Power BI dashboards on $45M+ in retail data to geospatial analysis across 180+ countries.

01📊
01

Retail Sales Performance & Profitability Analysis

Power BIDAXData ModelingStar Schema

An end-to-end retail analytics solution — interactive Power BI dashboards analyzing $45M+ in operational sales data across stores, districts, and product categories.

  • Designed a scalable star-schema model — Sales fact with Store, Item, District, and Time dimensions.
  • Built advanced DAX measures: Total Sales, Sales Variance %, Gross Margin, Sales per Sq Ft, YoY KPIs.
  • What-If analysis to simulate pricing changes and forecast revenue impact.
View on GitHub →
02🌾
02

Global Food Security & Climate Risk Analysis

PythonSQLFeature EngineeringGeospatial

Integrated multi-source datasets (FAOSTAT, World Bank WDI, emissions) across 180+ countries (1980–2023) to analyze food security, inequality, and supply stability.

  • Engineered Food Affordability Index and Nutrient Supply Score.
  • Identified 3 global food crisis periods; methane-heavy economies showed 25–40% higher price volatility.
  • Geospatial analysis classifying countries into risk tiers.
Read complete case study → GitHub ↗
03🔋
03

EV Adoption & Air Pollution Impact Analysis

PythonGeoPandasSpatial AnalysisFolium

Analyzed EV adoption, charging infrastructure, and PM2.5 pollution across 58 California counties — linking infrastructure investment to environmental outcomes.

  • Unified EPA and ARB datasets into a single GeoDataFrame.
  • Quantified up to 30% lower pollution in high EV-adoption regions.
  • Interactive Folium dashboards for regional planning.
View on GitHub →
View more projects →
Skills

What I work with

📊 Business Intelligence

Power BIDAXDashboardsKPI TrackingReporting Standards

🐍 Languages & Analysis

PythonSQLPandasNumPyExcel

🗄️ Data Modeling

Star SchemaData TransformationData ValidationData Governance

🗺️ Geospatial & Viz

GeoPandasFoliumMatplotlibSeaborn

🛠️ Tools

GitJupyter Notebook
Certifications

My Certifications

🎓

IBM Data Science Professional Certificate

IBM / Coursera — Python, SQL, data analysis, visualization, machine learning, and capstone project.

What's next

Let's turn data into decisions.

I'm actively seeking Data Analyst roles where analysis and visualization drive better business outcomes. My inbox is always open.

Get in Touch LinkedIn ↗