Summary
Asher Zafar is a Director of Data Science at Meta who specializes in turning ambiguous, high-stakes problems into operational ML and causal-inference solutions across VR and AI glasses products. Over 11 years he has built production demand-forecasting systems, designed audience-weighting frameworks for experimentation, and scaled double machine learning for content incrementality across global apps. His background blends public policy and data science—leading analytics teams in Ontario government, securing research grants at the Brookfield Institute, and consulting at Deloitte—so he routinely bridges technical rigor with policy and stakeholder-facing strategy. He is as comfortable building randomized-survey-derived signals as deploying industry-leading forecasting benchmarks, and he prioritizes problem framing as much as model choice. Based in New York, he brings a rare mix of econometric training and product-focused ML delivery that surfaces actionable decisions from messy, real-world data.
11 years of coding experience
12 years of employment as a software developer
BA, Economics, BA, Economics at The University of Texas at Austin
Master of Arts, Economics, Master of Arts, Economics at York University
English