Juan Orduz - Principal Data Scientist

Juan Orduz

Principal Data Scientist

Berlin, Germany

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Summary

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Rockstar

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Top School

Juan Orduz is a Principal Data Scientist based in Berlin with 9 years of experience applying rigorous mathematical training (PhD in Mathematics) to real-world forecasting, marketing analytics, and causal inference problems. He blends deep expertise in time series, Bayesian methods and causal inference with hands-on product and engineering experience, having deployed large-scale forecasting systems and led ad-tech modeling and bidder product roadmaps. An active open-source maintainer and contributor to flagship projects like PyMC, sktime and PyMC-Marketing, he builds tooling that bridges probabilistic research and production workflows (e.g., pushing Pandas support into PyMC and expanding sktime’s forecasting capabilities). Juan advises clients on Bayesian modeling, runs workshops, and shapes AI product vision while keeping close to code—setting up CI/CD, tests and reproducible examples across projects. Unusually for a practitioner at his level, he combines formal geometric-analysis training with practical skills in CI, visualization and reproducible notebooks, enabling both clear communication and robust deployment of complex statistical models.

9 years of coding experience

8 years of employment as a software developer

Doctor of Philosophy (PhD) Mathematics, Doctor of Philosophy (PhD) Mathematics at Humboldt-Universität zu Berlin

Universidad de los Andes

English, Spanish, German

Github Skills (29)

probabilistic-programming10

pytest10

python10

data-science10

scikit10

testing10

pandas10

machine-learning10

time-series10

marketing10

reinforcement-learning10

causal-inference10

forecasting10

arviz10

mcmc10

Programming languages (8)

TypeScriptRRustMakefileHTMLJupyter NotebookRubyPython

Github contributions (5)

pymc-labs/pymc-marketing

Mar 2022 - Mar 2023

Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.

Role in this project:

Data Scientist

Contributions:13 releases, 759 reviews, 97 commits in 1 year

Contributions summary:Juan primarily focused on establishing the development environment and implementing core functionalities within the repository. They set up the development environment, including CI/CD checks and pre-commit hooks, and updated the project to the latest PyMC version. Moreover, the user implemented and tested adstock transformations, and contributed to the documentation. The user's contributions directly align with the project's goal of providing tools for Bayesian marketing.

pythonclvpymctoolboxmarketing

pymc-devs/pymc-examples

Feb 2021 - Jan 2023

Examples of PyMC models, including a library of Jupyter notebooks.

Role in this project:

Data Scientist

Contributions:39 reviews, 15 commits, 10 PRs in 1 year 11 months

Contributions summary:Juan contributed to a PyMC3 example repository, focusing on reinforcement learning. Their work involved generating synthetic data, implementing a reinforcement learning model, and visualizing the results. The user made several revisions to improve the notebook's clarity and presentation, including correcting typos, improving the data generation process, and removing redundant sections. The user also added Bambi to resources.

pythonpymcjupyter-notebooknotebooksjupyter

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