Data Scientist / Machine Learning Engineer

Being part of the P&O Digital Delivery data group, you will apply your experience and familiarity with domain data processes to support the P&O organisation across teams such as Wells & Subsurface, Production and bp Solutions. These teams provides daily operational data management, data engineering and analytics support to this organisation across a broad range of disciplines, applications and business requirements. A data scientist applies scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Their key responsibilities include collecting and analyzing large sets of data, using machine learning algorithms, statistical models, and data processing techniques to predict future trends and provide actionable insights. A machine learning engineer designs and develops artificial intelligence (AI) systems that can learn and make decisions autonomously. Their key responsibilities include creating and optimizing machine learning models, developing algorithms that enable machines to perform tasks without explicit programming, and working with large datasets to train these models. They collaborate with data scientists, software engineers, and domain experts to implement machine learning solutions that address specific business needs. Additionally, machine learning engineers are responsible for ensuring the scalability and efficiency of machine learning systems, continuously improving model performance through rigorous testing and validation, and staying updated with the latest advancements in the field to integrate cutting-edge techniques into their work.

Our purpose is to deliver energy to the world, today and tomorrow. For over 100 years, bp has focused on discovering, developing, and producing oil and gas in the nations where we operate. We are one of the few companies globally that can provide governments and customers with an integrated energy offering. Delivering our strategy sustainably is fundamental to achieving our ambition to be a net zero company by 2050 or sooner!