Harnessing data science for a net-zero future.

At Shell, our data science team plays a pivotal role in fast-tracking our transition to net-zero emissions and preparing us for future energy solutions. Data Science at Shell involves not just technologies, algorithms, machine learning, programming languages, software, and database management, but also identifying problems to solve and transforms businesses and processes. Our team uses AI to derive real value from diverse data sources like blockchain, IoT devices, drones and petabytes of videos from land and marine surveys.

Organisations and teams capable of harnessing real-time data and delivering solutions that drive business value and accelerate energy transition will make a tangible impact in the field.

Data-driven Commercial Decisions

Commercial Data Science activities in Finance involve the application of data science techniques to generate valuable commercial insights for the business. Data scientists play a critical role in developing analytics models using specialised tools to address business problems and provide marketing analytics solutions. They are responsible for identifying appropriate models, evaluating their validity from scientific and business perspectives, and supporting the data science lead and digital product owners in project design and execution. Collaboration with stakeholders and subject matter experts is integral to their role, as they work closely with teams such as marketing and sales to ensure the models meet business needs. The commercial data scientists contribute to the development and implementation of effective data-driven strategies and decision-making processes, leveraging their expertise in data science and analytics to drive business success.

Data Science in Digitalisation

Shell's approach to digitalisation goes beyond technology, encompassing people and agile ways of working. The concept of "citizen data scientists" is embraced, recognising the potential of employees from diverse backgrounds, such as petroleum engineers or process engineers, who possess strengths in mathematics and science. Shell provides platforms, training, and a protected interface to enable these citizen data scientists to leverage AI and data science for developing tailor-made process solutions, including DIY (do-it-yourself) local no-code or low-code applications. This approach has gained momentum with over 500 live applications, empowering end-users to create software applications through simple drag and drop actions, without the need for writing complex code.

Furthermore, Shell has fostered a culture conducive to data science projects, with a robust network of over 7000 members in the Shell.ai network. This network aims to share knowledge and bridge the gap for end-users in understanding the value of data science and digital technology for their business.