Cornell Data Science (CDS) is an undergraduate project team that builds data-driven solutions to a variety of real-world problems. Current initiatives range from devising a scalable mapping system for better natural disaster response to developing a tool that can summarize Amazon reviews for a better user experience. Our team of 80+ students is a great place to meet people with diverse interests, gain experience at the intersection of theory and application, and contribute to greater community initiatives.

Cornell Data Science

Cornell Data Science's headquarters in Ithaca, United States

This department focuses on designing, developing, and maintaining software applications.

Software Development

This department focuses on the design, development, and implementation of machine learning models and systems.

Machine Learning Engineering

This department focuses on applying mathematical and statistical methods to analyze financial markets and develop investment strategies.

Quantitative Finance

This department focuses on the design, development, and management of data systems and infrastructure.

Data Engineering

This department focuses on analyzing and interpreting complex data to drive insights and inform decision-making.

Data Science

The Data Engineering Team at Cornell Data Science is responsible for designing, building, and maintaining the data infrastructure essential for various projects. This includes developing robust data pipelines, ensuring data quality, and facilitating efficient data access and storage. By collaborating with other teams, they enable the effective processing and analysis of data, driving innovative solutions for real-world challenges.

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Other teams

Machine Learning Engineering

Quantitative Finance

Data Engineering

Data Science

Data Engineering Team