Kuntal Malia

I started as a strategy consultant, but 20 years ago at Northwestern I found the problem that still fires me up: how to turn data into decisions that scale. Since then, I've built AI and data systems that drive revenue, margin, and competitive advantage. I established data science at ModCloth (acquired by Walmart), co-founded India's first AI-powered styling platform (100K+ users, 2x conversion), and now lead enterprise AI transformation at Metro Brands (900+ stores). One thing I firmly believe: AI is only valuable when it ships and when it sticks. What makes me different: I bridge the technical and the commercial. I can architect AI strategy, build ML models, AND translate both into P&L impact that CXOs and boards understand. I've operated at both extremes: built a zero-to-one AI company from scratch and led transformations at enterprise scale. My strength isn't just building AI, but operationalizing it so it becomes embedded in the business, not a side project that fades. Selected results: -Metro Brands: Built 2-year AI and Data roadmap spanning 900+ stores; launched pilots cutting execution time 60%; driving AI adoption from CXO to frontline -StyleNook (Co-Founder): Scaled India's first AI styling platform to 100K+ users; proprietary ML models drove 2x conversion, 50% lower returns, 45% repeat rate; pivoted during COVID (35% lower order cost, 1.6x frequency) -ModCloth: Established data science function supporting $100M+ growth; augmented intelligence models reduced inventory costs 25% while improving availability. How I add value: I work with organizations where AI transformation is mission-critical—proving it can drive commercial outcomes, embedding it at scale, or building the data foundations for competitive advantage. I thrive at the intersection of: ✔ Innovation-led growth: zero-to-one AI products and new business models ✔ Enterprise transformation: AI operating models, data modernization, governance at scale ✔ Cross-cultural leadership: US, India, UAE; startup agility meets corporate discipline ✔ Full P&L accountability: from strategy through execution to measurable outcomes The challenges that energize me: Zero-to-one AI products. Scaling from pilot to production. Modernizing legacy systems with GenAI. Building data capabilities that become competitive moats. Chief Data/AI Officer-level transformations where AI becomes the operating model.