Strategy · Product · Deployment
Arjuna Velayudam
Builder-minded strategist focused on improving decisions, workflows, and internal tools inside complex environments.
I like turning ambiguity into structured systems — working between data, product, and operators to get things shipped.
Where I've Built & Executed
A mix of high-intensity deal work, operational problem solving, and internal product building across finance and consulting.
- Automated recurring ops reports under tight SLAs.
- Analyzed trade flow patterns to flag anomalies.
- Worked across teams to de-bug data breaks quickly.
- Built cost and cash-flow models for distressed assets.
- Mapped operational KPIs to real levers on the ground.
- Helped teams prioritize actions in constrained timelines.
- Led design and rollout of a Deal Scenario Analysis Hub used across engagements.
- Helped build a sector metrics hub combining internal and market data.
- Worked directly with partners and clients to shape features and drive adoption.
Featured Deployments & Product Work
A deeper look at the tooling and decision systems I've helped design and deploy — from internal hubs in consulting to operator-facing analytics.
INTERNAL TOOL · DEPLOYED
Deal Scenario Analysis Hub
Internal web-based tool to quickly simulate standalone, synergy, and carve-out scenarios across deals, giving partners and teams a single place to reason about outcomes.
- • Defined must-have scenarios with partners & teams.
- • Aggregated and normalized financial & operational inputs.
- • Designed workflows non-technical users could navigate.
- • Iterated based on feedback to improve speed and clarity.
DATA PRODUCT · IN PROGRESS
Restaurant Tip & Performance Analytics
Prototype data product to quantify server performance and design a fair, incentive-aligned tip pool — giving operators a clearer picture of who drives revenue and why.
- • Synthetic PoS schema in PostgreSQL.
- • Python-based analysis for revenue & tip distributions.
- • Focus on metrics that feel fair and explainable to staff.
- • Grounded in real conversations with restaurant workers.