Sofia Pinto
Sofia is a principal data scientist at Nesta, working with the sustainable future mission team on decarbonising UK homes. During her time at Nesta, Sofia worked with energy performance certificates, social media and smart meter data to: estimate the cost of low carbon heating technologies, identify issues faced by homeowners in their low carbon heating path, understand how people consume energy in their homes and identifying the most suitable low carbon heating technology for groups of homes.
Prior to joining Nesta, Sofia worked as a data scientist at Imperial College London, assessing the accuracy of crowdsourced data for road traffic collision and injury surveillance. Before this she worked as a research fellow at the Social Physics and Complexity research group, LIP Portugal, on health related projects such as identifying antibiotic over-prescription and factors influencing it.
Sofia holds a Bachelor’s degree in Applied Mathematics and Master’s degree in Data Science and Advanced Analytics.
Session
Decarbonising UK’s home heating is one of the greatest challenges of the Net Zero transition, yet it currently relies on individual household decisions supported by government incentives. To help accelerate the local delivery, we are building tool that maps the most suitable low-carbon heating for clusters of properties at a neighbourhood level.
In this talk we will walk through our end-to-end data science pipeline, covering processing of large-scale geospatial data, the nuances of modelling where ground truth data does not yet exist, and how to translated local authorities needs into a functional product. We will present our Python tech stack and will conclude with a showcase of the user interface.
Whether you're interested in geospatial data engineering, machine learning for social good, or how to work within a multidisciplinary team, this talk offers a blueprint for building data products with real-world impact.