Manager, Data DeliveryPetSmart
Enterprise delivery leadership across data products, platforms, and AI-assisted ways of working.
DATA & AI TRANSFORMATION LEADER
From signalto scale.
I turn complex data into trusted decisions and lasting capability.
SELECTED TRANSFORMATIONS
Decisions that change the business.
Customer risk intelligence
Shaped the data and analytics capability behind a customer risk profile analyzer for wholesale banking in Singapore.
Content investment decisions
Turned ambiguous Akamai behavioral logs into evidence for digital bonus-content investment decisions.
Pricing & promotion strategy
Connected pricing, promotion, assortment, and effectiveness decisions through trusted data and analytics enablement.
Enterprise work anonymized
THE EXECUTIVE SERIES
Decisions before dashboards.
Short, evidence-led briefings on the business choices behind data, AI, and market performance.
EPISODE01
EXECUTIVE DECISION BRIEF
Target's Q2 Momentum
Watch on LinkedIn ↗THE PROFESSIONAL ARC
16+ years across engineering, consulting, enterprise delivery, and leadership.
Experience across India, Singapore, and the United States shaped a practical leadership style: technically grounded, commercially aware, and built for complex organizations.
Data leadership progressionPetSmart
Four roles since joining, with expanding scope across commercial data and delivery.
Consulting & analytics leadershipInfoCepts
Cross-industry programs spanning financial services, media, and enterprise analytics.
Early engineering foundationPersistent Systems
Built the technical grounding that still informs product and platform decisions.
EDUCATION & SELECT CREDENTIALS
- MBA, Organizational LeadershipEastern University · 2026 · GPA 3.88
- BE, Computer EngineeringUniversity of Pune
- Building Reliable Conversational Agents with GenieDatabricks Academy · 2026
- Forward ProgramMcKinsey.org · 2025
- Google Data Analytics · SAFe 5 PO/PM2022 · 2021
I still build.
Personal products that turn noisy information into a clear next decision.
01 / VALORA
Property intelligence from whatever you have.
Built to organize messy property inputs into sourced facts that a buyer can confirm before analysis begins. Maharashtra-first, with explicit evidence and risk boundaries.
GIVE US ANYTHING YOU HAVE
Drop anything.
The AI organises it.
Listing · brochure · RERA · notes
02 / WORTH IT?
A clearer answer before you buy.
A working AI deal advisor for marketplace listings. It turns a URL, image, or description into a value range, decision signals, and a practical negotiation starting point.
REAL AI DEAL & VALUATION ADVISOR
Know the value before you buy.
LISTING OR DESCRIPTIONEvaluate deal →
Real estateCarsTechCollectibles
Three transformations. One leadership pattern.
Make the signal useful.
Make the change last.
01
Wholesale banking · Singapore
Customer risk intelligence
CONTEXT
Risk signals lived across complex data and operating boundaries. Leaders needed a clearer, more consistent view of each customer before they could act with confidence.
THE DECISION
Frame the work around the decisions relationship and risk teams needed to make, then organize the data product around those moments.
MY OWNERSHIP
Led end-to-end product shaping and owned the data, analytics, and enablement work across an approximately 100-person cross-functional program.
WHAT CHANGED
Created a shared path from fragmented signals to an actionable customer risk profile, aligning product, data, analytics, and business teams around one operating outcome.
End-to-end product shapingData and analytics ownership~100-person cross-functional program
02
Global media
Content investment decisions
CONTEXT
A media business had rich delivery logs but no dependable way to understand whether digital bonus content changed audience behavior or justified further investment.
THE DECISION
Treat the logs as a behavioral evidence source, translate them into decision-ready measures, and connect usage patterns to the bonus-content portfolio.
MY OWNERSHIP
Owned the data and analytics enablement, from interpreting ambiguous event data through shaping the product questions and measurement approach.
WHAT CHANGED
Gave product and investment leaders a clearer basis for deciding which bonus experiences deserved attention, refinement, or reduced investment.
Ambiguous-log interpretationDecision-focused measurementCross-functional product enablement
03
Enterprise retail
Pricing & promotion strategy
CONTEXT
Pricing, promotion, and assortment choices touched many teams, while different data views made it harder to learn what worked and choose where to invest next.
THE DECISION
Build a dependable analytical foundation around the commercial questions: what to sell, how to price it, when to promote it, and how to measure effectiveness.
MY OWNERSHIP
Owned data, analytics, and AI enablement within an approximately 100-person cross-functional program, connecting strategy with delivery.
WHAT CHANGED
Established a more coherent decision system for commercial teams and a reusable foundation for evaluating pricing and promotion choices.
Commercial decision framingData and AI enablement~100-person cross-functional program
Strategy becomes real through the system around it.
My leadership operating system moves from decision framing to durable capability.
“The goal is not a smarter dashboard. It is a stronger decision, made repeatedly.”