London, England, United Kingdom
I am a Quant & Data Scientist, founder and CEO focused on building institutional-grade forecasting infrastructure for the economy. As Founder of Turnleaf Analytics, I work at the intersection of causality, machine learning and alternative data helping institutions move beyond simple models toward structured, validated forecasting systems. Over the past two decades, I have operated across quantitative research, live trading environments and large-scale team leadership. I have built and deployed models in production, managed multidisciplinary quant teams, and written extensively on probabilistic graphical models and causal AI. My work consistently bridges academic rigor and commercial accountability. At Turnleaf, we design forecasting systems as infrastructure — not research outputs. Forecasting, in my view, is not a model. It is a process, a product, and a responsibility. Alongside building Turnleaf, I continue to engage with the academic and institutional community through research, lecturing and applied collaboration. If you are focused on improving macro or inflation decision-making through disciplined, grounded systems, I am always open to thoughtful conversations.
Building MARCOS - the AI-Orchestrated Economic Forecasting Engine
• Helped Deloitte financial services clients to implement AI in their processes • Led the development and ongoing support of AI-enabled products and solutions • Supported clients with appropriate risk management frameworks for AI (e.g., trustworthy AI, interpretable AI) • Delivered thought leadership on AI techniques and technologies • Built the alternative data advisory offering for asset managers and insurers
• Taught “Graphical Models & Alternative Data” to MSc students in Mathematical Finance • Taught “Probabilistic Graphical Models” to students in "Artificial Intelligence: Cloud and Edge Implementations"
• Founded and expanded the Data Science teams to 25 Data Scientists spanning London and Bangalore • Created the procedures and appropriate committees for transitioning from POCs to Pilot and Product • Led to completion successfully 20+ data science projects leveraging the data assets of IHS Markit and spanning multiple data domains: Finance, Economics & Country Risk, Energy, Maritime, Aerospace & Defence, Automotive • Created the first alternative data trading signals and alternative data smart beta indices for the company • Deployed commercially 5 data science products: revenue >$5M / year • Founded and staffed the IHS Markit Academic Advisory Board comprising top academics and a PhD incubator to attract talent to IHS Markit • Acted as a thought leader for the company through strategic publications in peer-review journals, conference participations, university lectures