Naveen Venayak

Director, R&D Platform (Data Science, Software, Automation)

San Diego, California, United States
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Summary

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Senior
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Top School
Naveen Venayak is a Director-level AI and data platform leader in San Diego with 11 years of experience building data-driven R&D platforms for biotech. He has progressed from hands-on metabolic engineering and PhD research to leading multi-million-dollar LIMS and AI deployments that power $30M+ programs, blending lab automation, workflow modeling, and production-grade software engineering. Naveen specializes in integrating multi-omics and lab automation with scalable ML infrastructure—bringing models from hyperparameter tuning to routine deployment—and has a track record of creating high-ROI recommenders for DNA and protein design. He also designs data models and BI tooling that translate complex experimental data into strategy and cost forecasting, and he’s experienced in managing distributed, asynchronous teams. Notably, his background as a synthetic biologist/metabolic engineer gives him rare domain fluency that tightens the loop between wet lab experiments and ML-driven decision-making.
code11 years of coding experience
job7 years of employment as a software developer
bookDoctor of Philosophy (PhD) Chemical Engineering, Doctor of Philosophy (PhD) Chemical Engineering at University of Toronto
bookBiotechnology: Bachelor of Science (BSc) and Bachelor of Applied Chemistry (BASc) Biochemistry and Chemical Engineering, Biotechnology: Bachelor of Science (BSc) and Bachelor of Applied Chemistry (BASc) Biochemistry and Chemical Engineering at University of Ottawa
languagesEnglish, French
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Github Skills (19)

python9
jupyter-notebook8
multi-user8
ipython8
machine-learning8
data-science8
jupyterhub8
binderhub7
docker-container5
post-processing5
voila3
jupyterlab2
torrent2
jupyter2
dashboard2

Programming languages (4)

C++JavaScriptJupyter NotebookPython

Github contributions (5)

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nvenayak/impact

Sep 2015 - Jan 2019

The impact framework is designed to help scientists extract insight from experimental data in a transparent and reproducible fashion.
Contributions:334 commits, 7 PRs, 70 pushes in 3 years 4 months
scientistspythontransparentdata-sciencemachine-learning
nvenayak/Systemikon

Mar 2015 - Mar 2015

Contributions:5 pushes, 2 branches in 4 days
discoveryworkflow
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