Parul Pandey
Data Scientist • Author • Speaker
Hi, I’m Parul. I combine data science and developer advocacy to make machine learning accessible, responsible, and useful for real teams and communities. I’ve worked at H2O.ai (Principal Data Scientist) and Weights & Biases (Machine Learning Engineer). I co-authored an O’Reilly book titled Machine Learning for High-Risk Applications and regularly contribute to open-source projects and technical writing. I speak at conferences, mentor community programs, and write regularly.
Book
This book written with Patrick Hall and James Curtis, describes approaches to responsible AI—a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. It has also been translated into Korean and Chinese languages.
Kaggle Grandmaster | Notebooks
I earned the title of Kaggle Grandmaster in 2020, becoming the first woman in India and the second worldwide to reach this level in the Notebooks category. I enjoy explaining ideas and working with datasets, so this category felt natural to me. At my peak, I ranked 7th worldwide. My team also placed 6th in the WIDS Datathon.
My notebook Geek Girls Rising: Myth or Reality! won a prize in Kaggle's 2019 ML and DS Survey. I also won 2nd place in the Meta Kaggle Hackathon for my study of Kaggle's community growth, where I found signals linked to engagement and retention. My time on Kaggle has led me to speak at many Kaggle Days Meetups and guide participants in the 2021 Kaggle BIPOC Grant program.
Judge for Mozilla's Responsible Computing Challenge (RCC) in India
I was one of nine experts selected to judge the Responsible Computing Challenge (RCC) in India. The challenge aimed to equip technologists with a deep understanding of how technology and society intersect. As a judge, I helped select universities that integrated ethics into their curriculum to ensure graduates prioritize critical thinking, address inequality in technology, and build equitable systems.
Area Chair for the Ethics Section of Kaggle's AI Report 2023
I served as an Area Chair for the Ethics section of Kaggle's AI Report 2023, where I evaluated essays on ethical principles and risk mitigation strategies in machine learning applications.
