Operations Analyst
THE PROBLEM
Stuck between too complex and too small.
Enterprise operations run on systems that cost six figures and require a dedicated team to manage. Most small businesses know they need something better than spreadsheets and group chats — but they don't have the budget for enterprise software, and nobody on the team knows how to build an alternative.
So the work stays manual. Things fall through the cracks. Processes depend on whoever remembers to do them.
That's the gap I work in.
Most operations fall apart at the handoffs, the moments when work moves from one person, one system, or one step to the next. That's where the manual steps hide. That's where the things-people-have-to-remember live. That's where the friction accumulates.
My work starts with observation, not tools. I map what's actually happening in an operation before I design anything. Once I know where the gaps are, I build the automation layer that closes them, not to replace the people doing the work, but to remove the work that shouldn't require a person in the first place.
The principle is simple: people as the brain, AI as the hand.
I work around the tools you already have. The method doesn't change whether you're running on Notion or spreadsheets, Slack or email. The skill is knowing what a broken handoff looks like — not knowing your specific software.
BACKGROUND
I know what broken operations look like from the inside.
I spent six years running customer operations at a fintech company — managing the review pipeline, the inbound volume across calls, chats, and emails, and the gaps that nobody had documented. The enterprise tools were already in place. My job was everything the tools didn't cover: the handoffs with no owner, the processes that lived in someone's memory, the manual steps that created inconsistency at scale.
I built AI agents and automation systems to handle what the enterprise stack couldn't. Those same systems run in my own operation today.
I work with small businesses because that's where the gap is largest. The operation is complex enough to need systems. The team is too lean to build them.
Google Data Analytics Certificate · 6 years Customer Operations · AI Automation & Agent Design
Every operation I analyze breaks in the same sequence. The money has to move cleanly first. Then the delivery engine has to run without constant human intervention. Then the whole system has to be visible to the people making decisions. I work in that order, because building intelligence on top of chaos gives you a better-looking mess.
Phase 1 — Foundation
Revenue, billing, client intake — get money moving cleanly
Phase 2 — Work Engine
Delivery, capacity, time, scope — systematise how work gets done
Phase 3 — Intelligence
Dashboard, live data, forecasting — make the whole system visible
Linh Pham
Operations Analyst
I map how your business actually runs, find where the work breaks down, and build the AI systems that remove it.
© 2025 Linh Pham · Based in Canada · Remote Worldwide