Jonathan Mackenzie
Head Of Data Solutions (APAC)
Singapore
Summary
🤩
Rockstar🎓
Top SchoolJonathan Mackenzie is a seasoned data and media technology leader with 15 years’ experience driving programmatic, analytics and innovation across APAC, currently serving as Head of Data Solutions at Publicis Groupe in Singapore. He blends agency-side strategy and operational delivery—having built and scaled digital teams and offerings from the ground up—with deep technical chops rooted in a PhD-era focus on data mining and machine learning for traffic analysis. Jonathan is comfortable translating research-grade models into production-ready solutions and has contributed to notable open-source projects like hyperas (Keras + Hyperopt) and pyopencl, evidencing hands-on backend and data science expertise. He is known for connecting cross-market data talent and scaling repeatable, privacy-aware measurement and buying practices for global brands. Colleagues describe him as a pragmatic technologist who pairs experimentation with measurable business impact, and who still carves out time to “make cool things” outside of work.
15 years of coding experience
6 years of employment as a software developer
BA (Hons), European Studies with French and Italian, BA (Hons), European Studies with French and Italian at University of Bath
English, French, Italian
Stackoverflow
8,689reputation
1.6mreached
97answers
86questions
haskell
top-5%
latex
top-1%
Github Skills (22)
opencl10
python10
numpy10
hyperparameter-optimization10
keras10
latex10
parallel-computing10
data-science9
back-end-development9
haskell9
scientific-computing9
arrayobject8
machine-learning8
gpu7
html6
Programming languages (17)
Github contributions (5)
maxpumperla/hyperas
Sep 2016 - Dec 2019
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:11 commits, 4 PRs, 28 comments in 3 years 3 months
Contributions summary:Jonathan primarily contributed to the `hyperas` library, which focuses on hyperparameter optimization for Keras models. Their work involved modifying the optimization code to accept extra parameters, updating the code for improved functionality, and reverting the optim.py file. They also added a distributed example and a guide. These commits demonstrate a focus on core library functionality and integration of hyperparameter optimization with Keras models, highlighting skills in both back-end development and data science.
hyperopthyperparameter-optimizationkeras
inducer/pyopencl
Dec 2016 - Mar 2017
OpenCL integration for Python, plus shiny features
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 commits, 1 PR, 7 comments in 3 months
Contributions summary:Jonathan contributed to the OpenCL integration for Python by implementing and refactoring type mapping for OpenCL to numpy types. They created and updated documentation and added new vector types. Furthermore, the user fixed bugs and cleaned up the code, as well as removed `staticmethod` from cl vector functions. They also updated documentation for `enqueue_fill_buffer` and `enqueue_copy_buffer` and added a deprecation warning for a specific function.
openclpythongpuheterogeneous-parallel-programmingnvidia
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