Data Analyst

Chandana Yaraguntla

*****************@*****.*** / +1-940-***-**** / LinkedIn

EDUCATION

Master’s in Advanced Data Analytics May 2025

University of North Texas, Denton, TX

Relevant Coursework: Statistical Methods for Data Analytics, Data Mining, Data Visualization, Machine Learning Algorithms, Deep Learning with Big Data and Applications and Deployment of Advanced Analytics. Master’s in Business Administration Sep 2020

Qis College of Engineering and Technology, Andhra Pradesh, India TECHNICAL SKILLS

Statistical Analysis: Hypothesis testing, Regression Analysis, Decision Trees, Quantitative Analysis. HR Metrics: Workforce Analytics, Employee Engagement, Recruitment Performance Ad-hoc Reporting Programming Languages: Python, MySQL. coding

Business Intelligence and Reporting: Microsoft Excel, Pivot Tables, Tableau Prep and Tableau, Power BI, Matplotlib, Seaborn. Data Tools: OpenRefine, Excel, ETL processes.es

Cloud Platforms: Google Cloud Platform (GCP), Knowledge of AWS. PROFESSIONAL EXPERIENCE

HR ANALYST, VALUELABS Oct 2022 – July 2023

• Produced in-depth reports for internal HR teams and external stakeholders by thoroughly studying HR operations data for more than 500 employees, including hiring onboarding, training, performance management, and employee relations.

• Monthly candidate satisfaction increased by 20% as a consequence of my coordination and analysis of the interview process, which involved over 100 candidates. I also identified and fixed problems to guarantee a smooth interview process.

• Conducted periodic data uploads and audits to preserve data integrity.

• Ensured alignment and data-driven decision-making by coordinating daily updates and other HR-related tasks with the operations team, which resulted in a 25% increase in overall HR operational efficiency.

• Prepared informative reports by compiling and analyzing diverse HR data. Contributed to a 10% increase in workforce diversity by doing data analysis to maintain and develop the diversity information database. People Analytics TALENT ACQUISITION ANALYST, SAGEIT Oct 2020 – Sept 2022

• Oversaw talent acquisition analytics, which included gathering and analyzing data on finding candidates, setting interviews, and making selections, improved hiring productivity by 15%.

• Gathered and examined data from new hire papers for over 100 new hires, assisted with onboarding analytics, and accurately kept detailed employee files.

• Utilized various job portals and Applicant Tracking System (ATS) software to track and analyze candidate data, improving the efficiency and effectiveness of candidate shortlisting by 30%.

• Updated onboarding materials and handouts based on feedback and data analysis, maintaining accurate and timely candidate status and recruitment records, which enhanced the onboarding experience by 20%. ACADEMIC PROJECT

DATA ANALYSIS AND PREDICTIVE MODELING OF US MASS SHOOTINGS Oct 2023 – Nov 2023

• Analyzed over 10 years of mass shooting data, identifying 5 key factors such as the impact of mental health and various contributing reasons. Developed predictive models that led to a 20% improvement in prevention and responsive strategies.

• Used Open Refine to prepare and process over 50,000 records for further analysis and consistency. Created queries for 5 problem statements using GCP Big Query. GCP

GLOBAL EDUCATION ANALYSIS AND VISUALIZATION: ATTAINMENT AND ENROLLMENT Nov 2023 - Dec 2023

Utilized Tableau Prep for data analysis and cleaning of a global education dataset, containing information from 200+ countries, including education attainment, and enrollment rates in urban and rural areas for both male and female populations.

Performed in-depth analysis to identify trends and patterns, reviewing over 10,000 records. Created visually appealing dashboards in Tableau to communicate key findings, resulting in a 25% increase in data understanding. COMPREHENSIVE DATA ANALYSIS OF HOTEL BOOKING TRENDS Nov 2023 - Dec 2023

Conducted Exploratory Data Analysis (EDA) of a Hotel Booking dataset, containing 10,000+ records, including information about people booking hotels, hotel categories, and booking cancellation status.

Imported relevant libraries such as Pandas, NumPy, and Scikit-Learn in Python for data preparation, leading to a 30% reduction in data processing time.

Identified key trends and patterns in booking behavior and cancellation rates, contributing to strategies that reduced booking cancellations by 15%.

BIG DATA ANALYSIS OF AIR QUALITY MEASURES ACROSS THE USA Apr 2024 – May 2024

Applied EDA on a dataset with 10000+ records to analyze and identify outliers in the dataset and examined the relationship between air quality values and county-level factors using Ordinary Least Squares (OLS) Regression, Decision Tree, and KNN analysis, identifying key predictors of air quality with an R square of 0.85 for OLS regression.

Developed data visualizations using Matplotlib and Seaborn libraries, resulting in a 40% increase in understanding of the analysis.

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