The New York Data Science & AI Conference Presented by Lander Analytics
The New York Data Science & AI Conference
Presented by Lander Analytics
Workshops: Monday, August 25
Conference: Tuesday, August 26 & Wednesday, August 27
Location: New York City
Immerse yourself in the evolving world of data science and AI at The New York Data Science & AI Conference Presented by Lander Analytics—an intimate, single-track conference designed to connect data professionals and showcase world-class speakers. It will take place August 26 & 27, with hands-on workshops on August 25.
For over a decade, the New York R Conference has been the go-to event for R enthusiasts and data professionals. Now, as the field evolves, so does our conference. We continue to bring together data professionals from diverse industries such as technology, finance, healthcare, sports, retail, and more—fostering a space for exceptional content and unparalleled networking.
Attend in New York City and virtually to explore the latest advancements, share insights, and shape the future of data science and AI.
Got an idea for a talk? We'd love to hear it!
We're always excited to spotlight new voices and fresh perspectives.
Submit a TalkSpeakers
Andrew Gelman
Professor
Department of Statistics and Department of Political Science, Columbia University
Talk: What's Going On In There? Bayesian Tools for Understanding a Fitted Model
Danya Murali
Lead Data Scientist
Arbor
Talk: Leveraging Data Engineering and AI to Automate Energy Savings
Ben Lerner
CEO & Co-Founder
Espresso AI
Talk: AI with ROI: How to Use ML to Cut Your Snowflake Bill in Half
Max Kuhn
Scientist
Posit, PBC
Talk: Measuring LLM Effectiveness (Joint talk with Simon Couch)
Andrew Wallender
Data Editor
Bloomberg Industry Group
Talk: How to Use Free, Open-Source Text Embeddings to Accomplish Advanced Textual Analysis
Jon Sege
AVP, Data Management & Analytics
White Plains Hospital
Talk: From Prediction to Foundation: Deep Learning Models for Patient Care Optimization (Joint talk with Vincent Pan)
Ally Blake
Senior Coordinator, Football Data & Analytics
NFL
Talk: Simulating an NFL Game
Jared P. Lander
Chief Data Scientist
Lander Analytics
Talk: How I Learned to Stop Worrying and Love Vibe Coding
Chiraag Kala
Lead Data Scientist
Airbnb
Talk: Rethinking A/B Tests for Connected Users and Communities
Xilin Chen
Analytics Manager
Michigan Medicine
Talk: Using Quarto to Create Reports for Hospital Quality Improvement: Safely Lowering Cesarean Rates
Bill Gold
Head of AI
Citizens Bank
Talk: From Hype to Value: Mastering Gen AI Outcomes Through Evaluations
Abigail Haddad
Data Scientist/Machine Learning Engineer
Freelance
Talk: Processing Document Collections with LLMs: A Practical Workflow
Mike Band
Sr. Manager, Research & Analytics
NFL Next Gen Stats
Talk: How We Built It: An Offseason of Development at NFL Next Gen Stats
Daniel Chen
Post-Doc Research and Teaching Fellow & Data Science Educator
University of British Columbia
Talk: LLMs, Chatbots, and Dashboards: Visualize Your Data with Natural Language
Swaptik Chowdhury
Assistant Policy Researcher
RAND Corporation
Talk: Understanding Artificial General Intelligence Futures: Toward a Shared Vocabulary for Policy Planning
Vincent Pan
Data Scientist
White Plains Hospital
Talk: From Prediction to Foundation: Deep Learning Models for Patient Care Optimization (Joint talk with Jon Sege)
Simon Couch
Software Engineer
Posit, PBC
Talk: Measuring LLM Effectiveness (Joint talk with Max Kuhn)
More speakers coming soon…
Workshops
Machine Learning in R
Hosted by Max Kuhn
Monday, Aug 25 | 9:15am - 5:00pm
Join Max Kuhn on a tour through Machine Learning in R, with emphasis on using the software as opposed to general explanations of model building. This workshop is an abbreviated introduction to the tidymodels framework for modeling.
You'll learn about data preparation, model fitting, model assessment and predictions. The focus will be on data splitting and resampling, data pre-processing and feature engineering, model creation, evaluation, and tuning. This is not a deep learning course and will focus on tabular data.
Pre-requisites: some experience with modeling in R and the tidyverse (don't need to be experts); prior experience with lm is enough to get started and learn advanced modeling techniques. In case participants can’t install the packages on their machines, RStudio Server Pro instances will be available that are pre-loaded with the appropriate packages and GitHub repository.
(In-Person & Virtual Ticket Options Available)
Introduction of LLMs/AI
Hosted by Daniel Chen
Monday, Aug 25 | 9:15am - 5:00pm
There's a lot of hype around AI around all their use cases and the amazing things they can do. This workshop aims to demystify how LLMs work and give you a practical understanding of how they work and how to use them beyond the desktop application.
We will code with LLMs using an API and introduce two packages, chatlas (python) and ellmer (r), that make it easier to interact with LLMs programitaclly. We'll also see how we can use LLMs in Shiny dashboards to create a user interface with your own chat bots. We'll then expand on these basics to learn about RAG (retrieval augmented generation) and tool calling to give our bots more context and abilities to work as "agents". Finally, we'll see how we can use LLMs to help us work with our data science projects.
(In-Person & Virtual Ticket Options Available)
More workshops coming soon…
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