MSBA candidate at Santa Clara University with expertise in Python, R, SQL, ML, and analytics. Experience in research, NLP, and product analytics. Seeking data science opportunities in Silicon Valley.
My portfolio includes coursework and externships where I created dashboards, performed regressions, extracted insights, and designed AI workflows to generate actionable results.
A TruBridge externship focused on healthcare data analytics, exploring public health datasets and building dashboards and models to examine social determinants of health and infectious disease patterns.
Wayfair AI Agent Engineering for Business Intelligence Externship
Learn one of the most in-demand skills shaping the future of work: building AI agents. In this externship, you’ll step into the role of an AI Agent Developer and use n8n to design agents that think, plan, and act on real data — automating insights, decisions, and workflows. No coding experience required. By the end, you’ll create a live dashboard powered by your own AI agents, gaining hands-on experience that applies to any role or industry — from marketing and consulting to product management and data science.
Top performerAI Workflow DesignAI Agent DevelopmentPresentation SkillsWeb Scraping & Data Extraction
Analyzed Shopee marketplace performance for Nazava Water Filters to optimize promotional ROI, developing recommendations that improved visibility, conversion rates, and customer engagement.
MSBA candidate at Santa Clara University with expertise in Python, R, SQL, ML, and analytics. Experience in research, NLP, and product analytics. Seeking data science opportunities in Silicon Valley.
I’m Varsha Pai, currently pursuing an MS in Business Analytics at Santa Clara University. My journey includes research and analytics roles at SCU, externships with Beats by Dre, TruBridge, Wayfair, and Breaking Games, along with a recent internship at Box. I’m skilled in Python, R, SQL, machine learning, NLP, and visualization tools like Tableau and Power BI. I’m focused on expanding my network and gaining hands-on experience in data analytics, driven by a passion for transforming data into actionable insights.
Externships
SQL & Database Architecture Externship with Breaking Games
Breaking Games
Experience
Research Assistant
Santa Clara University Information Systems & Analytics Dept. · Aug 2025 – Present
Business Analytics Intern
Box (via SCU Industry Practicum) · March 2026 – May 2026
Education
Santa Clara University, Leavey School of Business
Master of Science in Business Analytics Candidate · Class of 2026
Santa Clara University
Bachelor of Science in Economics, Concentration in Data Analysis; Minor in MIS · Class of 2025
Skills
PythonRSQLMachine LearningEconometricsNLPStatistical AnalysisData CleaningOptimizationRetention AnalysisClaudeReplitGammaExcelTableauPower BIAI Agent Development
A TruBridge externship focused on healthcare data analytics, exploring public health datasets and building dashboards and models to examine social determinants of health and infectious disease patterns.
Data AnalysisGoogle Colab
Overview
The project analyzed county-level HIV outcomes alongside social determinants of health, selecting CDC BRFSS and AIDSVu datasets, cleaning and merging case and SDOH indicators, and producing visualizations and regressions that highlighted urbanicity and housing cost burden as notable factors. The work was awarded Top Performer by TruBridge.
I produced a cleaned, merged county-level dataset and analytical suite that included Python visualizations, regressions, a slide presentation, and an interactive dashboard comparing income and urbanicity against HIV prevalence.
Beats by Dre Data Analytics: Qualitative & Quantitative Insights Externship
A Beats by Dre data analytics externship focused on extracting qualitative and quantitative consumer insights from reviews and surveys.
Data AnalysisPythonAI & ML
Overview
During the Beats by Dre Data Analytics externship, I gained practical skills in analyzing consumer conversations and market trends. I utilized AI tools and data analytics techniques to uncover insights from customer feedback, perform sentiment analysis, and create impactful presentations. This experience deepened my understanding of consumer behavior and informed strategic decision-making
I produced a set of consumer-insight artifacts: a pain-point chart, an AIDA customer-journey spreadsheet, Google Sheets visualizations with thematic clusters, a Python sentiment and competitive analysis report, and a slide deck with prioritized recommendations for Beats Solo Buds.
Wayfair AI Agent Engineering for Business Intelligence Externship
Learn one of the most in-demand skills shaping the future of work: building AI agents. In this externship, you’ll step into the role of an AI Agent Developer and use n8n to design agents that think, plan, and act on real data — automating insights, decisions, and workflows. No coding experience required. By the end, you’ll create a live dashboard powered by your own AI agents, gaining hands-on experience that applies to any role or industry — from marketing and consulting to product management and data science.
AI Workflow DesignAI Agent DevelopmentPresentation SkillsWeb Scraping & Data Extraction
Overview
The work developed multiple AI agents and connected them into a Market Intelligence Dashboard, producing visual moodboards, trend reports, competitor analyses, and a content-strategy generator from live and archived data. The work was awarded Top Performer by Wayfair.
I produced production-ready visual prompts and AI moodboards, a downloadable PDF Consumer Trend report with a Loom demo, a consolidated competitor report with HTML output, and a content-strategy generator based on extracted market and competitor text.
Analyzed Shopee marketplace performance for Nazava Water Filters to optimize promotional ROI, developing recommendations that improved visibility, conversion rates, and customer engagement.
The externship converted six messy CSV exports from an e-commerce operation into a normalized analytics database and a Q4 dashboard. The work cataloged data sources, defined schema and transformation rules, and produced SQL queries used to populate analytics tables and drive dashboard metrics.
What I've accomplished
I inspected the available data sources, documented what each file contained, and established which business questions each dataset could support before building the schema and ETL.