Neal Richardson

Vice President, Engineering at Posit, PBC

nealrichardson

Software by Neal Richardson#

Events attended by Neal Richardson#

Posts and resources by Neal Richardson#

Data Science in Pediatric Cancer Research | Hubert Hickman | Data Science Hangout

ADD THE DATA SCIENCE HANGOUT TO YOUR CALENDAR HERE: https://pos.it/dsh - All are welcome! We’d love to see you! This week’s guest was Hubert Hickman, Senior Data Strategist and Data Operations Lead at the University of Chicago’s Data for the Common Good (D4CG)! Some topics covered in this week’s Hangout were building data solutions by staying close to the people who use them, harmonizing multi-center research data, working with rare disease data where datasets are small, and navigating a decades-long career across 16 programming languages and constant technological change. One community member asked: “What differences do you see between developing tools for a startup or for-profit organization versus developing things for the public good? Does that change how you think about who the customer is or what the focus of the product is?” (Note from Libby - what a fantastic question 🥹) Hubert’s paraphrased answer: In academic research you don’t have a product focus in the same way, but you still have customers, they’re just not outside paying customers, so you still have to pay attention to their needs. The key factor is distance. When you’re close to the people who contribute, manage, and use the data, like we are at the PCDC (Pediatric Cancer Data Commons), you build things that actually work for them. The further you get from the people who lay hands on your software, the more things tend to unravel. In large organizations you can lose the plot, where you’re 30 steps away just marking off tickets, and if the software is clunky people will use it anyway. That’s not an environment I could live in for very long. Resources mentioned in the video and chat: HamClock Launcher (Hubert’s open-source ham radio side project) → https://github.com/huberthickman/HamClockLauncher R for Data Science (free online book) → https://r4ds.hadley.nz/ Introduction to Statistical Learning (ISLR) → https://www.statlearning.com/ Data Science Learning Community (DSLC) → https://dslc.io/ The Epidemiologist R Handbook → https://epirhandbook.com/en/ Tidy Text Mining with R book (Julia Silge) → https://www.tidytextmining.com/ R Graph Gallery → https://r-graph-gallery.com/ TidyTuesday (open datasets) → https://github.com/rfordatascience/tidytuesday YaRrr! The Pirate’s Guide to R → https://nathanieldphillips-yarrr.share.connect.posit.cloud/ Statistics Globe YouTube Channel → https://www.youtube.com/@StatisticsGlobe Riffomonas YouTube Channel → https://www.youtube.com/@Riffomonas Statistics 1 with R (Leiden) → https://poweleiden.github.io/statistics1/ “The Great Awakening of Agile Engineering” (Neal Richardson blog) → https://enpiar.com/2026/07/06/the-great-awakening-of-agile-engineering/ posit::conf 2026 Registration → https://conf.posit.co/2026/ ► Subscribe to Our Channel Here: https://bit.ly/2TzgcOu Follow Us Here: Website: https://www.posit.co Hangout: https://pos.it/dsh The Lab: https://pos.it/dslab LinkedIn: https://www.linkedin.com/company/posit-software Bluesky: https://bsky.app/profile/posit.co Thanks for hanging out with us! Timestamps: 00:00 Introduction 07:32 “Could you tell me a little bit about how you met that friend? Did you join a community like this one? What did that look like?” 09:34 “I’m wondering what advice you would give somebody who is coming in new to the game and is being tasked with building a data solution for somebody?” 11:30 “I’m wondering if you have seen AI-driven development shift the building-bespoke-stuff game a little bit?” 14:08 “What was your favorite programming language and your least favorite programming language, and why?” 16:55 “Are R and Python the languages that you prefer for data science more specifically, versus other software engineering tasks and things of that nature?” 19:31 “What does an average day look like for you? Or maybe an average week, if every day is not the same?” 22:47 “What differences would you think of or see between developing tools for a startup or a for-profit organization, versus developing things that you’re doing for the public good?” 26:33 “What was your biggest struggle starting a company?” 30:12 “Any introduction to R classes or resources that people would recommend to someone who is just starting out?” 33:22 “What types of problems in cancer research presently most pique your curiosity from a math/stats perspective, and how do you think about approaching them with data?” 37:10 “Is there an infrastructure you use when working with collaborative multi-center data without actually sharing the data, for example DataSHIELD, or another way for federated data?” 43:40 “I was wondering if you would like to share at all about your side projects, specifically your ham radio ham clock launcher?” 47:39 “Do you have a piece of career advice for us? Something that you wish you had been told, or something that you have just found helpful for you over your career?”

Julia Silge, Neal Richardson

Hosting MCP servers securely with Posit Connect

Model Context Protocol (MCP) is a hot topic in AI tooling right now, and there is a lot of noise about the benefits of using it for AI projects, but less information that addresses the security questions or when it’s the ideal tool for the job. Join Neal Richardson and Matt Leary for a practical look at when MCP is the right fit, when to reach for something else like skills or command-line utilities, and how to deploy MCP servers in a way that actually improves your security posture. We’ll also show how Posit Connect implements these principles with a live walkthrough of Connect’s MCP hosting architecture. What you’ll learn: -When MCP is the right choice for your AI project -How MCP fits into the broader AI tooling landscape -Why Connect is a secure place to host your MCP servers -How to deploy MCP servers on Connect via a real-world use case demo More MCP Content from our blog: Why Connect is a great place to host your MCP servers: https://posit.co/blog/hosting-mcp-servers-on-connect?utm_source=youtube&utm_medium=social&utm_campaign=701Qg00000vOw6uIAC&utm_term=connect&utm_content=mcp-webinar MCP Servers on Connect: Managing credentials and access: https://posit.co/preview-link/node/15401/905c2506-84cb-4e95-93fd-f096a1789883?utm_source=youtube&utm_medium=social&utm_campaign=701Qg00000vOw6uIAC&utm_term=connect&utm_content=mcp-webinar More on Posit Connect: https://posit.co/products/enterprise/connect

Neal Richardson

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny RMarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr Github Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education Rstats Open Source Oss Reticulate

MCP, or Not MCP — Neal Richardson | AI in Production 2026

MCP, or not MCP? When the Model Context Protocol is the right tool for your LLM — when it isn’t — and how to use it in a way that improves your security posture. Presented by Neal Richardson (Posit Software, PBC) at AI in Production 2026 — The Catalyst, Newcastle, 5 June 2026. ABOUT THE TALK Model Context Protocol is a standard for defining tools that can be made available to your LLMs, whether in an IDE assistant, a command line utility like Claude Code, or other AI applications. There’s a lot of noise out there about what you should use to get the best results from AI, and it can be hard to keep straight all of the new jargon that is thrown around. So in this talk, I will break it down and provide some guidance on when you should use MCP, and when you should probably reach for some other tool. I will provide some examples of cases where MCP is the right tool for the job, and when other things, like skills or other context files, are better. I will also devote attention to questions of security, as well as authentication, which are important for MCP. Some critics of MCP have argued that they are a security risk, and I’ll discuss why that is. Then, I will show how you can use MCP servers in a way that actually improves your security posture and will delight your IT admins. SPEAKER Neal Richardson — Posit Software, PBC: https://posit.co/ GitHub: https://github.com/nealrichardson/ LinkedIn: https://www.linkedin.com/in/enpiar/ Website: https://enpiar.com ——————————————— AI in Production is Jumping Rivers’ conference for data scientists, ML engineers and AI practitioners building and deploying AI & ML in the real world. The inaugural event was held at The Catalyst, Newcastle Helix, on 4–5 June 2026. Event & full programme: https://ai-in-production-2026.jumpingrivers.com/ ▶ More talks from the conference: https://www.youtube.com/@jumping-rivers Full playlist — every AIP 2026 talk: https://www.youtube.com/playlist?list=PLGqNj9r9d0Q8 Organised by Jumping Rivers: https://www.jumpingrivers.com/ With thanks to our sponsors — Databricks, Posit, the Royal Statistical Society, Chapman & Hall/CRC, and the National Innovation Centre for Data. Community partner: DevITJobs.uk. #AIinProduction #AIP2026 #MachineLearning #LLMs #AIEngineering

Neal Richardson

Neal Richardson - MCP, or not MCP | Pydata London 26

Neal Richardson - MCP, or not MCP | Pydata London 26 \Model Context Protocol is a standard for defining tools that can be made available to LLMs and AI applications. There’s a lot of noise out there about what you should use to get the best results from AI, so in this talk, I will provide some guidance on when you should use MCP, and when you should reach for some other tool. I will describe cases where MCP is the right tool for the job, and when other things, like skills or other context files, are better. I will also devote attention to questions of security and authentication, which are important for MCP, and provide concrete examples of how MCP servers can be used to unlock agentic workflows while also strengthening data governance. This talk is intended for those who are interested in using LLMs for workflows involving data. No prior experience with MCP is required. Outline: Intro: how can I get data from this API into my Claude Code session? What is MCP? When should you use it, when should you use other tools Work through an example Sharing and deploying MCP servers, alternatives and best practices Optimizing your tools for best results www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Neal Richardson

Neal Richardson | Bigger Data With Ease Using Apache Arrow | RStudio

The Apache Arrow project enables data scientists using R, Python, and other languages to work with large datasets efficiently and with interactive speed. Arrow is so fast at some workflows that it seems to defy reality–or at least the limits of R’s capabilities. This talk examines the unique characteristics of the Arrow project that enable it to redefine what is possible in R. The talk also highlights some of the latest developments in the arrow R package, including how you can query and manipulate multi-file datasets, and it presents strategies for speeding up workflows by up to 100x. About Neal: Currently Director of Engineering at Ursa Labs / RStudio. Previously led product and engineering at Crunch.io. Ph.D. in Political Science from the University of California, Berkeley

Neal Richardson

rstudio Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny RMarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Ggplot2 Tibble Readr Stringr Tidyr Purrr Github Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Forcats Rstats Open Source Oss Reticulate Neal Richardson Apache Apache Arrow Big Data

Neal Richardson | Accelerating Analytics with Apache Arrow | RStudio (2020)

The Apache Arrow project is a cross-language development platform for in-memory data designed to improve system performance, memory use, and interoperability. This talk presents recent developments in the ‘arrow’ package, which provides an R interface to the Arrow C++ library. We’ll cover the goals of the broader Arrow project, how to get started with the ‘arrow’ package in R, some general concepts for working with data efficiently in Arrow, and a brief overview of upcoming features

Neal Richardson

rstudio Rstudio::conf(2020) Neal Richardson Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny RMarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr Github Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Rstats Open Source Oss Reticulate Apache Arrow

Neal Richardson

Software by Neal Richardson#

dplyr

reticulate

Shiny for Python

purrr

renv

actions

sparklyr

pak

Events attended by Neal Richardson#

AI in Production

PyData London 2026

Posts and resources by Neal Richardson#

Data Science in Pediatric Cancer Research | Hubert Hickman | Data Science Hangout

Hosting MCP servers securely with Posit Connect

MCP, or Not MCP — Neal Richardson | AI in Production 2026

Neal Richardson - MCP, or not MCP | Pydata London 26

Neal Richardson | Bigger Data With Ease Using Apache Arrow | RStudio

Neal Richardson | Accelerating Analytics with Apache Arrow | RStudio (2020)