EDP wanted to maximize new solar panel installations with spatial models to identify areas with the highest customer propensity in order to target geomarketing campaigns.
Using Random Forest (RF) models & KMeans we were able to calculate expected installation numbers at postcode granularity, using socioeconomic & climate data to enrich existing internal CRM data.
Vodafone wanted to include twin area functionality in their Vodafone Analytics solution, allowing their B2B clients to identify similar behaviour patterns by location using footfall data.
Our Data Science team developed a similarity score, calculating the distance between cells with a L2 norm on a principal component space - tackling missing values following an ensemble probabilistic approach.
Gallatin County (Montana) wanted to provide precise information about land water rights and available wells for Real Estate operations.
An intuitive solution for all members of their Real Estate association in which they can explore and navigate across different counties, pulling information about parcel owners.
Understand how customers move in shopping malls, allowing them to find products and stock availability, guiding them to their favorite brands (e.g. offering them help from a shop assistant).
Two mobile apps using indoor maps and analytics in which customers get the fastest route to their destination, or where they can get customized offers based on their purchase records.
Build a robust route optimization engine that could be used by logistics customers, covering different generic constraints.
A platform in which hundreds of thousands of routes are optimized every day. A simple web interface that shows routes and planned stops every day, for every driver and every type of vehicle.
Ramping up a team to solve complex problems spatially at the pace that business needs dictate is challenging.
In particular, Spatial Data Scientists are hard to find: there are 4 Data Science job postings for every Data Scientist in the market.
Limited geospatial expertise to scope, define, and deliver complex projects.
Our data scientists, geographers, computer scientists, designers, and engineers have over 180 years of combined experience solving geospatial problems across the globe.
Our 25-strong team of Spatial Data Science experts are ready to hit the ground running.
With over 80 Enterprise organizations served, our team knows what it takes to unlock the power of spatial analysis and can fast track your projects.
Whatever the maturity of your organization, or the nature of your use case - our team can help:
Our Professional Services team allows you to fast-track strategic geospatial projects, no matter the scope of your challenge, using CARTO’s stack for advanced Data Science projects or even developing customized apps.
With a PhD in Ocean & Earth Science, Giulia has significant experience in statistical downscaling & creating predictive algorithms. She has worked with a range of clients including WeWork, Globalia & Vodafone.
Spatial Data Scientist
Passionate about solving spatial problems, Cayetano has extensive experience in open source geo technologies working with technologies such as GDAL, PostGIS & much more. Cayetano has architected cutting-edge solutions for clients such as Mastercard and El Corte Ingles.
Having designed hundreds of geospatial applications for clients such as Renault, Mastercard, DPD and Vodafone, Jose is an expert in creating compelling user experiences - considering the many nuances of enterprise use cases in different territories.
Having carried out research with MIT's Department of Earth, Atmosphere & Planetary Sciences, Álvaro has significant experience carrying out complex geospatial analysis - not only in the environmental field but also with clients such as Vodafone.
Spatial Data Scientist
Using spatial data science & technology, Matt works to find solutions to business questions by understanding the role that space & place have on businesses across many industries. Having worked in geospatial for 10 years, he is an award-winning cartographer with degrees in Geography & Sociology from the University of Wisconsin - Madison.
Director of Spatial Data Science