Benjamin Vincent
Director at InferenceWorks Ltd
United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolBenjamin Vincent is a Director and causal Bayesian data scientist with 12 years of applied experience who leads InferenceWorks Ltd and serves as Principal Data Scientist at PyMC Labs. A former academic with 15 years of faculty experience and a DPhil in Computational Neuroscience, he translates decision‑making research into practical Bayesian and causal solutions for business problems. As a core PyMC contributor and developer of CausalPy, he specializes in quasi‑experimental methods like Bayesian synthetic control and regression discontinuity, publishing reproducible notebook examples used by the PyMC community. Benjamin combines deep statistical theory with production‑oriented tooling, routinely generating simulation‑driven visualizations and refined model code that bridge research and real‑world inference.
12 years of coding experience
3 years of employment as a software developer
DPhil, Computational Neuroscience, DPhil, Computational Neuroscience at University of Sussex
Github Skills (14)
bayesian-statistics10
regression10
pymc10
bayesian10
python10
bayesian-data-analysis10
bayesian-inference10
causal-inference10
data-analysis10
jupyter-notebook9
data-visualisation9
data-visualization9
pandas9
data-visualizations9
Programming languages (13)
Github contributions (5)
pymc-labs/CausalPy
Sep 2022 - Jan 2023
A Python package for causal inference in quasi-experimental settings
Role in this project:
Data Scientist & PyMC Modeler
Data Scientist & PyMC ModelerContributions:25 releases, 264 reviews, 381 commits in 4 months
Contributions summary:Benjamin appears to be a data scientist contributing to a causal inference package. Their commits focus on implementing Bayesian synthetic control models, suggesting expertise in causal inference. The user’s work involves generating and analyzing simulated data, creating visualizations, and refining model code within the PyMC framework, with examples provided in notebook form.
causal-inferencepythonpymcquasi-experimentalquasi-experiments
pymc-devs/pymc-examples
Jan 2021 - Dec 2022
Examples of PyMC models, including a library of Jupyter notebooks.
Role in this project:Data Scientist
Data ScientistContributions:71 reviews, 83 commits, 92 PRs in 1 year 11 months
Contributions summary:Benjamin primarily contributed to the development and enhancement of examples within the PyMC examples repository, focusing on models for handling truncated and censored data, as well as a regression discontinuity design. They implemented and refined notebooks covering topics like Bayesian regression, generalized linear models, and counterfactual inference. The user also updated model implementations, and refined existing notebooks for the gallery.
jupyter-notebookpymc
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