Enterprise data, turned into decisions that hold up in the boardroom.

I lead the establishment of Universal Music Group's Finance BI & Analytics Center of Excellence, part of a global transformation of the finance function. My teams own the finance reporting data model — the metric definitions, hierarchies, and calculation logic that make a single source of truth possible — and deliver the standard reporting, dashboards, self-service, and AI capabilities behind performance management and executive decision-making across 60+ countries, multiple labels, and genuinely different operating models. Much of the work is the unglamorous kind that decides everything: consolidating fragmented reporting tools onto one enterprise platform, and making the numbers reconcile to global consolidated results.

Before UMG I was VP and Global Head of Data, Analytics, and the Global Capability Center at Mattel, leading a 125+ person global organization on Google Cloud and building a capability center in India from my own proposal to the CTO and CFO. Earlier, fourteen years at Verizon, finishing as Director of Data Science for the Business Analytics COE — a COE whose creation traced directly back to the FP&A transformation I had led as its global process owner. Before that, the consulting years at KPMG, where I learned the craft of asking hard questions politely.

My conviction is that analytics succeeds as an operating discipline, not a science fair. The interesting work is rarely the model; it is the governance, the data quality, the operating rhythm, and the patience to make a metric mean the same thing in every meeting. I am genuinely enthusiastic about AI, and equally enthusiastic about knowing where it does not belong. For a few years I also taught executive masterclasses in data and AI at Caltech, which remains the most efficient known method of discovering what one does not actually understand.

Away from the dashboards I am a committed spectator: of Carnatic music in Chennai's December season, of sport in most of its forms, and of the occasional perfectly engineered couplet by Ogden Nash.