Experience
"Is there a faster, better way to do this?" — This one question has shaped every role I've held. From my first Excel macro to the full-stack AI dashboard running in production today, it's the instinct that turns me from an analyst doing the work into an engineer eliminating it.
My e-commerce career started at Wissend Consultancy, managing catalogs for brands like Lenovo and Duraflame across Amazon and Walmart. Within weeks of joining, I'd written a CMD script that renamed thousands of product images in seconds — a task that would have consumed days of manual work. Management noticed. That was the moment I realized: this wasn't a one-off hack — it was how I wanted to work.
Today at ATHIBAN Ecommerce PVT LTD, I've grown into an E-commerce & Automation Specialist. I led the complete TECHATRON brand launch across three countries — sourcing from China, navigating BIS and ESMA compliance, building SEO-optimized listings for Amazon India, UAE, USA plus Flipkart and Noon, and setting up full FBA integration. In parallel, I ship Python tools, Chrome extension suites, and full-stack dashboards — including AdInsight Pro, the Amazon Ads audit platform I built solo that turns a 4-hour manual PPC review into a 90-second upload-to-insight loop.
What sets me apart is my instinct to solve problems with code. When I see a repetitive task, I don't do it twice — I automate it. When I see scattered customer feedback, I don't skim it — I build an AI-powered app to analyze every review at scale. When I see a 16-hour audit, I don't grind through it — I replace it with a 5-minute script. That mindset is how I deliver results that go beyond traditional catalog management — and how I turn problems that most teams accept as "just how it is" into ones that are already solved.
Three Principles That Guide Everything I Ship
Automate First, Then Execute
Before I do a task twice, I ask whether I should do it at all. Most "this is just how we work" processes are really automation opportunities waiting to be named. I surface them, scope them, and ship the fix.
Ship, Don't Prototype
I don't build proofs-of-concept that sit in a folder. Every tool I write runs in production — used by real people on real workflows, stress-tested against thousands of SKUs and messy real-world data. Working beats polished.
Data Makes the Decision
Every optimization I recommend is backed by numbers — ACoS trends, review sentiment patterns, audit failure rates, campaign structure metrics. Opinions are optional. Data isn't.