Jared Lander

Jared P. Lander is the founder and chief data scientist of Lander Analytics, a New York-based data science and artificial intelligence consulting and training firm. As chief data scientist and founder, Lander assists organizations in developing practical, measurable AI workflows grounded in robust data foundations. He holds a master's degree in statistics from Columbia University and a bachelor's degree in mathematics from Muhlenberg College, with experience spanning academic research and industry. His areas of expertise include data management, multilevel models, machine learning, generalized linear models, data visualization, and statistical computing.

In addition to his work at Lander Analytics, Lander serves as an adjunct professor at Columbia Business School and a visiting lecturer at Princeton University. Course material from his Columbia classes is integrated into his corporate training programs, bridging academic rigor with real-world application. His writings on statistics are available at jaredlander.com, and his work has appeared in Forbes and the Wall Street Journal.

Lander is the author of "R for Everyone," a book on R programming designed for data scientists and non-statisticians. The book is recognized as a resource in the data science community for making complex statistical concepts accessible. As an R Consortium board member, Lander is active in the global data community and frequently speaks at conferences, universities, and meetups worldwide.

Lander organizes the New York Open Statistical Programming Meetup, the world's largest R meetup, as well as the New York R Conference and R Conferences in New York, Washington DC, and Dublin. His conference work brings together data scientists from government, defense, NGOs, and industry. Lander's talks, including "How I Learned to Stop Worrying and Love Vibe Coding" at the New York Data Science and AI Conference and ODSC West, reflect his ongoing engagement with advancements in AI and data science.