Dane Laban
Principal Data Scientist
Sydney, New South Wales, Australia
Summary
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Senior🎓
Top SchoolDane Laban is a Principal Data Scientist based in Sydney with nine years of experience building audience forecast models for broadcast and online media using big data and deep learning. He leads the team behind Nine’s 9Predict product, shipping production-grade Python, Spark and Airflow pipelines at scale. Dane combines a strong research pedigree—a PhD in atomic/molecular physics and postdoc experience designing ultrafast experiments—with practical optimisation work in industry, giving him a knack for translating complex physical and statistical models into robust, operational systems. He is comfortable across the stack from data acquisition and streaming to model deployment and experiment design, and has a history of improving data fidelity and capture rates in high-throughput environments.
9 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Atomic/Molecular Physics, Doctor of Philosophy (Ph.D.), Atomic/Molecular Physics at Griffith UniversitySQL, SQL at CodecademyMachine Learning (via Coursera), 96.4%, Machine Learning (via Coursera), 96.4% at Stanford University
English
Github Skills (43)
monitor10
python10
data-science10
data-engineering10
machine-learning10
workflow-engine10
apache10
scheduler10
etl10
automation10
mlops10
orchestration10
data-integration10
data-pipelines9
apache-airflow9
Programming languages (2)
Github contributions (5)
TheZepto/airflow
Feb 2019 - Jan 2022
Apache Airflow
Contributions:5 pushes, 2 branches in 2 years 11 months
apacheairflowapache-airflow
TheZepto/Car_Counter
Jun 2017 - Oct 2017
Contributions:32 pushes, 1 branch in 3 months
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