Director, Data Science & Machine Learning

MS - Economics & Computation, Duke University

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Learning Collider’s lead data scientist, Nitya Raviprakash, is a seasoned data-for-good practitioner. From robust data analytics to AI engineering, Nitya draws on experience garnered from The Alan Turing Institute and Microsoft. 

Nitya is skilled with wrangling large and complex datasets and understanding the intricacies therein. For example, as a Turing Data Science for Social Good Fellow, she worked collaboratively with her cohort and World Bank researchers to detect corruption using publicly available data and machine learning tools.

Nitya now flexes her data and collaborative superpowers across Learning Collider projects. She manages multiple Workforce-related datasets, builds models for algorithmic fairness, and guides the organization in establishing best practices for data processing and analysis.

At home and at work, she exudes calm and open-mindedness, often sharing her workspace with fostered felines. She often has insights on the best chai, filter coffee, and good eats she and her partner find in the Bay Area.