PyMC Bayesian Model Guidance

I’m at the model-building stage of a Bayesian project and need a short, focused consultation with someone who knows PyMC inside out. The aim is to shape the model architecture, choose sensible priors and likelihoods, and confirm that my sampling strategy will converge cleanly. I already have the data prepared and a rough notebook in place; what’s missing is expert feedback that can save me from identifiability issues, divergent transitions, or unnecessary computational cost.

Ideally we’ll share screens (or code) for a live walkthrough, refine the model together, then wrap up with a brief written summary or an annotated notebook so I can keep iterating confidently on my own. If you have a strong track record building PyMC models and enjoy explaining the why as well as the how, let’s set up a session.