MOHAN SAI BONTHULA

Business Analytics Professional

Arlington, US.

About

Highly analytical Business Analytics professional with a Master's degree and hands-on experience in predictive modeling, AI-driven automation, and cross-functional data strategy. Proven ability to translate complex data into actionable insights, having reduced procurement efficiency by 25% and enhanced search accuracy by 30% through advanced ML and NLP techniques. Skilled in Python, SQL, Power BI, and Agile methodologies, driving data-driven decision-making and delivering significant operational improvements.

Work

Neviton Limited

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Business Analyst Intern

, , US

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Summary

Drove operational efficiency and data-driven decision-making by developing analytical tools and optimizing processes for procurement analytics.

Highlights

Developed a Python-based vendor recommendation engine integrated with Power BI, reducing product-related issues by 40% across 500+ items.

Optimized XGBoost-based vendor scoring logic, enhancing end-to-end procurement cycle efficiency by 25%.

Designed and implemented a Power BI dashboard for 15+ teams, streamlining procurement processes and improving task efficiency by 30% through KPI prioritization.

Optimized multi-table SQL queries, including CTEs and window functions, processing over 3 million records to enhance procurement analytics capabilities.

Orchestrated ETL pipelines utilizing Azure Data Factory and Azure APIs to seamlessly ingest procurement data into Power BI datasets.

The University of Texas - Arlington

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Data Analyst Intern at UTA Libraries

Arlington, Texas, US

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Summary

Enhanced data extraction, recommendation systems, and team productivity through advanced analytics and project leadership.

Highlights

Automated research data extraction through 15+ complex SQL queries, accelerating project timelines by 40%.

Enhanced book recommendation precision by 25% using NLP-based semantic search (TF-IDF + cosine similarity) and fine-tuned transformer embeddings.

Led sprint planning and backlog grooming for a 4-member analytics team, improving delivery predictability by 20%.

Cyient Limited

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Data Analyst

Hyderabad, Telangana, India

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Summary

Improved data consistency, reporting efficiency, and strategic operations through SQL development, BI dashboard creation, and predictive modeling.

Highlights

Developed and optimized SQL scripts for ETL processes, ensuring data consistency and accuracy for large datasets in European transportation projects.

Created Power BI dashboards to visualize supply chain KPIs and performance metrics, enhancing reporting efficiency across multiple departments and reducing manual procurement analysis effort by 30%.

Led predictive modeling projects that informed strategic operations, resulting in a 15% increase in inventory turnover.

Education

The University of Texas at Arlington

Arlington, Texas, United States of America
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Masters Business Analytics with Data Science Concentration Grade:

Courses

Python Programming

Cloud Computing

Data Mining

Data Science

Data Warehousing & Business Intelligence

Economic Forecasting

Evidence-Based Management

Capstone Project

Awards

Outstanding Student Employee Award

The University of Texas at Arlington (UTA)

Awarded for exceptional performance and dedication as a student employee.

Certificate of Exceptional Performance

Google Developer Groups

Received for exceptional performance.

Wall of Fame Recognition

Cyient

Recognized for outstanding contributions to project success.

Certificates

Corporate Analyst Development Program (CADP)

JPMorgan Chase & Co.

Data Visualization with Tableau

UC, Davis

Skills

Programming Languages

Python, SQL, R, SAS, HTML, CSS.

Data & BI Tools

Tableau, Microsoft Power BI, MS Excel, SAS Enterprise Miner.

Machine Learning & AI

Regression, Vertex AI, Vector-Search, Spanner, Random Forest, Classification Models, NLP, XGBoost, TF-IDF, Cosine Similarity, Transformer Embeddings, Ensemble Learning, SVM.

Cloud & Data Engineering

AWS, Database Management, Azure API, Azure Data Factory (ADF), ETL, ELT.

Projects

Stroke Risk Prediction Using Ensemble Learning and Patient Data Analysis

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Summary

Developed a stacked ensemble model (Random Forest, SVM) for predicting stroke risk from patient data.

Data-Driven Box Office Predictions: Unlocking Insights for Netflix Success

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Summary

Spearheaded a machine learning initiative to analyze over 5,000 Netflix titles using random forest algorithms.