Chetan Injavarapu

Summary

Data Science graduate with hands-on experience in operations analytics, Power BI dashboard development, and data modeling. Proven ability to analyze operational datasets, build KPI-driven reporting solutions, and support data-driven decision-making. Experienced in cross-functional collaboration, data validation, and maintaining reporting standards to improve operational efficiency and business performance.

Education

Rutgers University — Camden, NJ

GITAM University — India

Professional Experience

Building Manager (Operations) — Housing & Residence Life, Rutgers University

• Managed day-to-day building operations supporting resident services, facility coordination, and operational workflows.
• Acted as primary point of contact for operational issues, resolving service requests and escalating critical incidents.
• Collaborated with cross-functional teams including maintenance, security, and administration to ensure service efficiency.
• 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.
• Ensured compliance with operational policies, safety standards, and service quality expectations.

Data Science Intern — ACME GRADE

• 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 key performance indicators (KPIs) and communicated results through visualizations and reports.
• Ensured data quality, validation, and governance practices during preprocessing and analysis.

Data Science Experience

Retail Sales Performance & Profitability Analysis | Power BI, DAX, Data Modeling

• Developed and deployed interactive Power BI dashboards analyzing $45M+ operational sales data across stores, districts, and product categories.
• Designed scalable star-schema data model integrating Sales (fact) with Store, Item, District, and Time dimensions.
• Built advanced DAX measures including Total Sales, Sales Variance %, Gross Margin, Sales per Sq Ft, and YoY KPIs.
• Performed multi-level operational analysis identifying top/bottom performers and regional sales trends.
• Implemented What-If analysis to simulate pricing changes and forecast revenue impact.

Global Food Security & Climate Risk Analysis | Python, SQL, Feature Engineering, Geospatial

• Integrated multi-source datasets (FAOSTAT, WDI, emissions) across 180+ countries (1980–2023).
• Engineered Food Affordability Index and Nutrient Supply Score to quantify food security and inequality.
• Identified 3 global food crisis periods; methane-heavy economies experienced 25–40% higher price volatility.
• Applied geospatial and trend analysis to classify countries into risk tiers for policy insights.

EV Adoption & Air Pollution Impact Analysis | Python, GeoPandas, Spatial Analysis, Folium

• Analyzed EV adoption, charging infrastructure, and PM2.5 pollution across 58 California counties.
• Integrated EPA and ARB datasets into a unified GeoDataFrame enabling large-scale geospatial analysis.
• Quantified up to 30% lower pollution levels in high EV adoption regions.
• Built interactive dashboards using Folium to support regional planning and data-driven decision-making.

Technical Skills

Languages: Python, SQL

Business Intelligence: Power BI, DAX, Dashboard Development, KPI Tracking, Reporting Standards

Data Analysis: Pandas, NumPy, Excel, SQL (Joins, Aggregations)

Data Modeling: Star Schema, Data Transformation, Data Validation, Data Governance

Tools: Git, Jupyter Notebook

Certifications

IBM Data Science Professional Certificate — IBM / Coursera