First an electrical engineer, then a geophysicist and now a data scientist. For some people this may seem very different but for Mercia they were very natural moves: All focused in mathematics, data, coding and on solving practical problems. She is originally from Brazil, likes running outdoors, travelling to encounter new places, culture and experience different food.
Developing and gaining trust in a robust model that meets the specific demands of an organisation, iterating it into a usable product. These are the real challenges that data scientists face when implementing machine learning within enterprise organisations. Discover how one of our lead Data Scientists solved these challenges for a major oil and gas firm. Our data scientists face an array of challenges implementing machine learning within enterprise organisations. Creating a top-notch model is not necessarily up there, in fact it's maybe even the easy bit.
This story isn't going to spin a tale of neural networks, complex predictive problems and arrays of graphics cards in the cloud (that's one for another time). Instead it's about the reality of applying data science in big business. It's about winning the trust of hundreds of highly skilled experts who will use the predictions in their line of work. It's about using technical solutions and a deep understanding of the domain and users to guarantee success.