Varsha Srinivasan
Data Analyst @Walmart
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WORK HISTORY
Data Analyst @Walmart
US
LLM-Based Product Content Analysis:• Analyzed outputs from large language models (LLMs) used to generate product titles, descriptions, and short descriptions for merchant listings.• Measured adoption of LLM-generated content, merchant satisfaction, and usage frequency, and reported insights to both merchants and the LLM development team.• Used Python (NumPy, Matplotlib, NLTK, etc.) to perform analysis and sentiment analysis and generate daily performance reports, scheduled via in-house Walmart Cloud Native Platform (WCNP).Shipping From Club (SFC) Initiative:• Implemented the end-to-end workflow for Sam’s Club’s Shipping from Club (SFC) initiative, including eligibility determination for clubs, shipping classifications (hazmat and non-hazmat), and daily job scheduling for item selection.• Built Django-based APIs and React components to support merchant operations, and integrated final item outputs into Azure File Storage for downstream usage and reference.Merchant Data Workflows: • Worked with Sam’s Club merchant data to build workflows that identifies trending items for display on the e-commerce platform based on the seasonal dates and merchant choice.Automated reporting and monitoring processes to ensure accuracy and visibility of items surfaced to the website.• Designed and developed a React-based dashboard that consolidates insights from multiple initiatives like trending items, SFC, and Gen AI initiative, providing merchants with interactive charts and key metrics for decision-making.
EDUCATION
San José State University
Master's degree, Data analytics
Rajalakshmi Engineering College
Bachelor's degree, Computer Science
ABOUT VARSHA SRINIVASAN
Data Analyst with 5+ years of industry experience building AI-driven analytics platforms, scalable data pipelines, and merchant decision systems at Walmart / Sam’s Club. Specialized in translating complex business requirements into automated, data-backed solutions using Python, SQL, GenAI, and cloud-native architectures. Experienced in driving data quality, workflow efficiency, and operational scalability through data modeling, advanced analytics, and merchant-facing dashboards, with a strong focus on production reliability, performance optimization, and measurable business impact.
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