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Sam Hawkins is a Data Programme Director at Ember at Ember. He possess expertise in energy, science, sustainable energy, statistics, sustainability and 15 more skills.
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Data Programme DirectorEmber Nov 2023 - PresentLondon, England, Gb -
Data LeadEmber Nov 2022 - Dec 2023London, England, Gb
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Senior Data ScientistVattenfall Aug 2011 - PresentSolna, Stockholm, SeI specialise in anything which requires meteorological insight and data, and in general take the output from Numerical Weather Prediction (NWP) models, and do machine-learning magic with them. A large part of my work is developing and applying machine learning algorithms for forecasting of renewable energy generation. Working with weather data from multiple NWP models, I combine this with real-time streaming data from renewable generators, using python and cloud computing platforms to develop, train and deploy scaleable machine learning models to support seasonal, day-ahead and intraday power trading. I carry out detailed verification of both deterministic and probabilistic forecast models to identify opportunities for improvement. I work with a wide variety of machine learning and AI methods to support the transition to a fossil-free energy system: other examples include solar forecasting, heat-load forecasting, and optimisation of industrial battery usage. -
Phd ResearcherUniversity Of Edinburgh Oct 2007 - Feb 2012Edinburgh, GbPhD project on variability of UK wind resource. I used the Weather Research and Forecast (WRF) model to create an 11-year high resolution (3km) hindcast of the UK and surrounding coastal waters. The results were extensively verified against all available in-situ weather stations and remote sensing data. The hindcast was then used to create hourly patterns of wind generation from a future high-wind penetration energy system, and matched to patterns of electricity demand. The results allowed detailed analysis of how wind might be integrated into the UK's energy system, and gave critical insight into e.g. how frequently we might face prolonged situations of low wind, and the impact of large amounts of wind power on security of supply. -
Project OfficerScottish Institute Of Sustainable Technology (Sistech) Mar 2005 - Sep 2007Edinburgh, GbDeveloping small scale renewable projects with rural communities in the Scottish Borders. I was Involved in all stages of project from bid-writing, through to final presentations.I also contributed to a Scottish Government review of the potential for small-scale hydropower to contribute to renewable energy targets. -
Research OfficerPolicy Studies Institute 2004 - 2005London, GbI supported energy-economic modelling using the MARKAL model, to help inform energy policy at the time. I also carried out a review and critique of the possible role of hydrogen as an energy vector in a sustainable energy economy, which was published as a book chapter. -
InternshipIbm Jun 2002 - Aug 2002Armonk, New York, Ny, UsExtreme Blue programming internship to build an cloud accounting web-service using Apache axis and SOAP
Sam Hawkins Skills
Sam Hawkins Education Details
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The University Of EdinburghAtmospheric Sciences And Meteorology -
University Of CambridgeComputer Science
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University Of StirlingSustainable Development
Frequently Asked Questions about Sam Hawkins
What company does Sam Hawkins work for?
Sam Hawkins works for Ember
What is Sam Hawkins's role at the current company?
Sam Hawkins's current role is Data Programme Director at Ember.
What is Sam Hawkins's email address?
Sam Hawkins's email address is sa****@****all.com
What schools did Sam Hawkins attend?
Sam Hawkins attended The University Of Edinburgh, University Of Cambridge, University Of Stirling.
What are some of Sam Hawkins's interests?
Sam Hawkins has interest in Weather, Skiing, Science, Cycling, Creativity, Climbing, Nature, Geekery, Mountains.
What skills is Sam Hawkins known for?
Sam Hawkins has skills like Energy, Science, Sustainable Energy, Statistics, Sustainability, Sustainable Development, Python, Data Analysis, Wrf, Sql, High Performance Computing, Weather Forecasting.
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