Oliver Parson
Product Data Science Lead
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolOliver Parson is a Product Data Science Lead and machine learning specialist with 12 years’ experience applying advanced ML to decarbonisation and energy optimisation across utilities and IoT. He combines a PhD in computer science and deep research roots in non-intrusive load monitoring with hands-on delivery of scalable ML products at companies like Bulb, Hive and National Grid. Comfortable splitting time between coding and leadership, he has led teams, set roadmaps and deployed models at scale using cloud tooling (GCP/AWS) while mentoring engineers through periods of high change. An active open-source contributor, he helped enhance the NILMTK toolkit by adding new disaggregation metrics and state-based evaluation, reflecting a taste for rigorous, reproducible evaluation. Based in London, he’s focused on turning research-grade methods into production systems that reduce carbon and unlock value from smart meter data.
12 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of Southampton
Github Skills (5)
pandas10
algorithms10
python10
metric10
data-analysis9
Programming languages (3)
Github contributions (5)
nilmtk/nilmtk
Dec 2013 - Jan 2020
Non-Intrusive Load Monitoring Toolkit (nilmtk)
Role in this project:
Data Scientist
Data ScientistContributions:38 commits, 3 PRs, 30 pushes in 6 years 2 months
Contributions summary:Oliver contributed to the project by adding metrics for evaluating the performance of disaggregation algorithms. They introduced a new metric, "Fraction of Energy Correctly Assigned," including its mathematical definition and documentation. Furthermore, the user added state-based metrics such as precision, recall, and F-score for performance evaluation. The commits also indicate the user worked on bug fixes within the existing metrics.
forecastingpythonnilm-algorithmsnilmelectrical-engineering
oliparson/cat-detection
May 2020 - Jul 2020
Detect whether a cat is in the house using photos taken by a Raspberry Pi
Contributions:54 pushes in 2 months
raspberry-pipythonhouseraspberrydetect
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