I build the connection between technical depth, market context, and product judgment — so a complicated system turns into a decision someone can actually make.
01 — A business mind with technical roots
I am interested in the moment a complicated system finally becomes a clear choice.
Computer Science and Data Science at VIT gave me the discipline to build. At BigHaat, live work in search, automation, pricing, and operations gave that build a customer and a consequence.
My MBA is widening the lens across product, markets, marketing, and strategy — so the question is no longer only can we build it? but what is worth building, and why?
Current chapter02 — Selected work
01AI + DATA SCIENCE
Image-led product discovery flow for an agri-commerce context, helping shoppers move from visual intent to product language.
02AI + DATA SCIENCE
RAG-style lookup for product and internal PDFs so repeated document questions did not keep becoming manual work.
03Business Intelligence
Crawled 9 competitor sites, matched products fuzzily, and surfaced price movement as a business signal.
04Automation & Operations
Hourly anomaly layer for BigHaat order movement, designed to surface unusual shifts earlier in the day.
05Automation & Operations
Automated content collection workflow that made publishing more consistent and useful for a farming audience.
03 — Capability system
A wider working range than a tools list: research, product judgment, AI systems, engineering, and the clarity to bring them together in one recommendation.
From customer friction to a sharper value proposition.
Reading the category, the customer, and the competitive signal.
Applied AI only where it removes a meaningful unit of effort.
Turning uneven operational data into something a team can act on.
Building the workflow end to end, not just proving the concept.
Making the recommendation carry as much weight as the analysis.
04 — Experience
Product, marketing, strategy, and consumer behaviour. Academic Excellence in the top 10% of the 2025-26 batch year.
Applied AI across search, pricing intelligence, document automation, anomaly detection, and logistics visibility — shipped into live agri-commerce operations.
First proof that data work changes shape when inputs are live, teams move fast, and the output has to help somebody act today.
CGPA 9.15/10 with a Data Science specialisation. 500+ algorithmic problems solved alongside coursework.
05 — Field notes
06 — Outside the resume
