Narasimha Royal

About Me

Master’s

Computer Science
University of Houston

Expected: 2026

🎓 Bachelor's

Computer Science & Engineering
New Horizon College of Engineering

L e t ' s T a l k

L e t ' s T a l k i n g

I'm Narasimha Royal, MS Computer Science candidate at University of Houston, graduating May 2026.

I build dashboards and analysis that help people make faster decisions. At Zensar Technologies, I wrote SQL queries across 500K+ record databases to flag delivery bottlenecks, built Power BI dashboards that cut weekly reporting from 4+ hours to 30 minutes, and automated data cleaning pipelines in Python

Since then, I've built an NLP pipeline analyzing sentiment across 44.2M Amazon reviews, designed interactive Power BI dashboards for 449K+ federal wage records, and analyzed 1M+ NVIDIA stock records in Excel and Tableau.

Currently a Graduate Teaching Assistant at UH Bauer College, where I coordinate data deliverables across 10+ project teams and translate technical work into clear, stakeholder-ready outputs.

Open to full-time Data Analyst roles starting June 2026.

Experience

Current

Graduate Teaching Assistant

C. T. Bauer College of Business — UofH

Aug 2025 – Present

10+ teams 70+ students Weekly reporting

Tracked and analyzed project milestones across 10+ teams using spreadsheets, monitoring deliverables, deadlines, and performance metrics to ensure on-time client delivery.
Coordinated data collection from 70+ students and nonprofit clients, consolidating progress reports into weekly status summaries for faculty review.

Data Analyst

Data Analyst Intern

Zensar Technologies — Bengaluru, KA

Jun 2023 – Mar 2024

500K+ rows 3 Power BI dashboards 4h → 30m

Analyzed delivery performance data across 500K+ records using SQL (JOINs, CTEs, window functions) to identify bottlenecks and flag at-risk projects for leadership.
Built 3 Power BI dashboards with DAX measures tracking KPIs, turnaround time, SLA compliance, weekly volume trends, used in stakeholder reviews.
Automated data cleaning pipeline in Python (Pandas) for recurring datasets, reducing manual prep time from 4+ hours to 30 minutes weekly.