About us
PyMC Labs: The Bayesian Consultancy
PyMC is a probabilistic programming library for Python that allows users to fit Bayesian models using a variety of numerical methods, most notably Markov chain Monte Carlo (MCMC) and variational inference (VI). Its flexibility and extensibility make it applicable to a large suite of problems. Along with core model specification and fitting functionality, PyMC integrates with ArviZ for exploratory analysis of the results.
In this Meetup we will discuss topics related to PyMC, statistics, Python, Bayesian Analysis, to name a few.
We also will discuss use cases of PyMC in the business world.
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Contact
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If your company uses PyMC and would like to share about it with our community, please email us: info@pymc-labs.com
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PyMC Labs
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Website: https://www.pymc-labs.com
YouTube: https://www.youtube.com/c/PyMCLabs
LinkedIn:ย https://www.linkedin.com/company/pymc-labs/
Twitter:ย https://twitter.com/pymc_labs
PyMC Open Source: https://www.pymc.io/
Upcoming events
1

Agentic Data Science: How to engineer trust into Analytics and Modeling agents
ยทOnlineOnline๐๏ธ Speakers: Thomas Wiecki PhD, Luca Fiaschi, PhD, Benjamin Maier, PhD, Evan Wimpey | โฐ Time: 15:00 UTC / 8:00 AM PT / 11:00 AM ET / 4:00 PM Berlin
The emerging field of Agentic Data Science aims to automate the entire modeling lifecycle, from hypothesis to decision. But this introduces a challenge far greater than standard code generation: It is infinitely harder to build a reliable data scientist than a reliable coder.
In software, if the code passes tests, it works. In data science, an agent can write bug-free Python that executes perfectly, yet still produce garbage inference. The challenge isnโt syntax; itโs reasoning through uncertainty, confounders, and the messiness of real-world data.
In this session, the PyMC Labs team opens the hood on how we design agents that can do reliable science. Weโll cover the engineering reality of building agents that can handle the ambiguity of modeling without hallucinating confidence.
Youโll learn:
- Why data science agents fail differently and how to catch errors when the code runs fine but the conclusions are wrong.,
- How to evaluate agentic reasoning for statistical validity, robustness, and causal consistency.,
- Practical approaches to testing, validation, guardrails, and deciding when human-in-the-loop is required,
Join us for a technical, practitioner-led discussion on deploying agentic data science that survives contact with real-world data.
๐ Outline of Talk / Agenda:
- 5 min: Introduction to PyMC Labs and speakers
- 40 min: Panel discussion
- 15 min: Q&A
๐ผ About the speakers:
Dr. Thomas Wiecki (Founder of PyMC Labs)
Dr. Thomas Wiecki is an author of PyMC, the leading platform for statistical data science. To help businesses solve some of their trickiest data science problems, he assembled a world-class team of Bayesian modelers and founded PyMC Labs - the Bayesian AI consultancy. He did his PhD at Brown University studying cognitive neuroscience.๐ Connect with Thomas:
๐ Linkedin: https://www.linkedin.com/in/twiecki/
๐ Website: https://www.pymc-labs.com/
https://twiecki.io/
๐ GitHub: https://github.com/twiecki
๐ Twitter: https://twitter.com/twieckiDr. Luca Fiaschi (PyMC Labs Partner, Gen AI Vertical)
Luca helps organizations unlock the value of data and AI. With 15+ years of experience, heโs led and scaled teams at Mistplay, HelloFresh, Alibaba, and Stitch Fix, driving breakthroughs in personalization, marketing optimization, and causal modeling. He holds a PhD in Computer Science from Heidelberg University.๐ Connect with Luca:
๐ Linkedin: https://www.linkedin.com/in/lfiaschi/
๐ Github: https://github.com/lfiaschiDr. Benjamin Maier (Principal Data Scientist)
Ben develops mathematical models of complex systems and the software frameworks used to learn from them. He has over a decade of experience across academia, government, and industry, working on large-scale statistical and mechanistic models for real-world decision-making. He holds a PhD in Theoretical Physics from Humboldt University of Berlin.๐ Connect with Ben:
๐ Linkedin: https://www.linkedin.com/in/benjaminfrankmaier/
๐ Github: https://github.com/benmaier๐ผ About the Host:
Evan Wimpey (Director of Analytics at PyMC Labs)
Evan helps clients design Bayesian solutions tailored to their goals, ensuring they understand both the how and why of inference. With masterโs degrees in Economics and Analytics, he focuses on delivering clear value throughout projects and brings a unique twist with his background in data comedy.๐ Connect with Evan:
๐ Linkedin: https://www.linkedin.com/in/evan-wimpey/
๐ GitHub: https://github.com/ewimpey๐ Code of Conduct:
Please note that participants are expected to abide by PyMC's Code of Conduct.๐ Connecting with PyMC Labs:
๐ Website: https://www.pymc-labs.com/
๐ฅ LinkedIn: https://www.linkedin.com/company/pymc-labs/
๐ฆ Twitter: https://twitter.com/pymc_labs
๐ฅ YouTube: https://www.youtube.com/c/PyMCLabs
๐ค Meetup: https://www.meetup.com/pymc-labs-online-meetup/
๐ฎ Discord:37 attendees
Past events
44


