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.
--------------------------------------
Contact
--------------------------------------
If your company uses PyMC and would like to share about it with our community, please email us: info@pymc-labs.com
--------------------------------------
PyMC Labs
--------------------------------------
Website: https://www.pymc-labs.com
YouTube: https://www.youtube.com/c/PyMCLabs
LinkedIn: https://www.linkedin.com/company/pymc-labs/
Twitter: https://twitter.com/pymc_labs
PyMC Open Source: https://www.pymc.io/
Upcoming events
2

Marketing Foundation Models Bayesian MMM Without Per-Dataset Fitting
·OnlineOnlineBuilding a trustworthy Bayesian marketing mix model (MMM) takes a lot of skilled, repetitive work. Someone has to choose a structure, fit it, diagnose it and revisit the assumptions, then do it all again for the next brand, market or quarter. And because the reported uncertainty depends on the one structure the modeler picked, it is usually too narrow.
In this session, Carlos Trujillo and Teemu Säilynoja present Marketing Foundation Models (MFM): a model trained on simulated marketing worlds that estimates baseline, channel and control contributions, with uncertainty, in a single pass, without fitting a model to each new dataset. They will walk through how it works, what the evaluation on synthetic data shows, and where this early research prototype still falls short. Luca Fiaschi hosts, with time for your questions.
What you will learn:
- How MFM combines a simulator of marketing worlds, a transformer encoder and flow matching to return contribution estimates without per-dataset fitting.
- What the synthetic evaluation found: channel contribution error about a quarter of a standard PyMC-Marketing MMM's, and better calibrated uncertainty than standard regression.
- Why sampling over causal structures gives more honest uncertainty than a single hand-built model.
- The model's known limits today, and how it differs from foundation models such as TabPFN and TimesFM.
Who should attend:
- Marketing science and analytics teams that already run MMMs, or have been put off by how long they take to build.
- Data scientists working on Bayesian modeling, causal inference or amortized inference.
- Analytics leaders who want measurement answers inside the planning cycle.
📜 Outline of Talk / Agenda:
- 5 min: Introduction to PyMC Labs and speakers
- 40 min: Panel discussion
- 15 min: Q&A
💼 About the speakers:
Dr. Luca Fiaschi (PyMC Labs Partner, Gen AI Vertical)
Luca helps organizations unlock the value of data and AI. With 15+ years of experience, he’s 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.Connect with Luca 👉 LinkedIn
Carlos Eduardo Trujillo Agostini (Principal Data Scientist at PyMC Labs)
Carlos is a Marketing Scientist passionate about using data and AI to turn marketing strategy into measurable results. He’s worked with teams across Latin America, Europe, and Africa, including roles at Wise, Bolt, and Omnicom Media Group. As a core member of PyMC Labs, he contributes to open-source projects like PyMC-Marketing, blending statistical rigor with practical marketing insight.Connect with Carlos: 👉 LinkedIn
Teemu Säilynoja (Principal Data Scientist at PyMC Labs)
Teemu Säilynoja is a data scientist with expertise in Bayesian modeling, marketing analytics and trading analytics. He is completing a Doctor of Science degree focused on calibration assessment of Bayesian models. He also contributes to open-source tools for probabilistic programming and model evaluation in Python and R.Connect with Teemu: 👉 LinkedIn
------------------
📖 Code of Conduct:
Please note that participants are expected to abide by PyMC's Code of Conduct.Connecting with PyMC Labs:
🌐 Website: https://www.pymc-labs.com/
👥 LinkedIn: https://www.linkedin.com/company/pymc-labs/
🐦 Twitter: https://twitter.com/pymc_labs
🎥 YouTube: https://www.youtube.com/c/PyMCLabs
🎮 Discord: https://discord.gg/MARSCNemw343 attendees
Ask Me Anything: Marketing Analytics with PyMC Labs Experts
·OnlineOnlineBring your toughest marketing analytics questions to two PyMC Labs principal data scientists. There are no slides and no prepared talk: this hour is an open Ask Me Anything, and the agenda is whatever you ask, from marketing mix modeling (MMM) and model validation to budget allocation and measuring incrementality.
The session works the way our Expert Access Program (EAP) works with client teams: you bring the problem, and our experts work through it with you. It is the first of a monthly series of open sessions with PyMC Labs experts.
Who should attend
- Marketing analytics and data science teams building or running an
- MMM Marketing and finance leaders who use MMM results to set budgets
- Teams weighing Bayesian MMM or PyMC-Marketing for their measurement stack
💼 About the speakers:
Teemu Säilynoja (Principal Data Scientist at PyMC Labs)
Teemu Säilynoja is a data scientist with expertise in Bayesian modeling, marketing analytics and trading analytics. He is completing a Doctor of Science degree focused on calibration assessment of Bayesian models. He also contributes to open-source tools for probabilistic programming and model evaluation in Python and R.
Connect with Teemu: 👉 LinkedInTimothy McWilliams (Principal Data Scientist at PyMC Labs)
With over 7 years of experience in the marketing mix modeling and marketing analytics space, Tim specializes in applying Bayesian modeling techniques to solve complex business challenges and uncover actionable insights. Passionate about bridging advanced statistical methods with real-world marketing strategy, he has worked across diverse industries to optimize media investments and measure impact.Connect with Tim: 👉 LinkedIn
------------------
📖 Code of Conduct:
Please note that participants are expected to abide by PyMC's Code of Conduct.Connecting with PyMC Labs:
🌐 Website: https://www.pymc-labs.com/
👥 LinkedIn: https://www.linkedin.com/company/pymc-labs/
🐦 Twitter: https://twitter.com/pymc_labs
🎥 YouTube: https://www.youtube.com/c/PyMCLabs
🤝 Meetup: https://www.meetup.com/pymc-labs-online-meetup/
🎮 Discord: https://discord.gg/MARSCNemw316 attendees
Past events
55


