Data Scientist

Education Requirements • Degree in a STEM field; Ph.D. preferred (ideally in geophysics or geology). • Mastery in Deep Learning, Reinforcement Learning, and multimodal large language models. • Strong programming experience with PyTorch or TensorFlow. Roles and Responsibilities The Data Scientist will become part of a dynamic Data Science team in the newly established Data Science and ML Capability Center (CC), under the Information, Data and Analytics (IDA) team within the IT Digital Engineering leadership. The Data Scientist will be responsible for developing, deploying, and supporting data science solutions and products in an agile setting across various business challenges for an oil and gas multinational. Key responsibilities include: • Creating full-stack data science applications/tools on digital platforms. • Delivering data science products at production scale. • Managing the lifecycle of data science products from development through to support. • Transforming proofs of concept into larger deployable products for the oil and gas multinational and scaling successful solutions across multiple projects and assets. • Collaborating with P&T Research teams to convert proofs of concept into scalable data products. • Adhering to digital quality initiatives by conducting regular health checks, audits, and code reviews, to ensure the delivery of clean, maintainable, production-level code. • Evaluating and benchmarking new asset-related initiatives before developing solutions. • Contributing to community building initiatives such as Centers of Excellence (CoE) and Communities of Practice (CoP). Key Characteristics • +6 years of experience as a Data Scientist with clear evidence of Deep Learning Research. • Accountability for the delivery and maintenance of data science solutions. • Ability to cross-pollinate successful ideas and methodologies across projects. • Strong commitment to quality standards and continuous improvement. Mandatory Skills • Machine Learning and Statistical Modelling (Mastery) • Exploratory Data Analysis (Skilled) • Core Programming Skills & Languages (Skilled) • AI Engineering Essentials (Skilled) • DevOps and Agile Methodologies (Skilled) • Cloud deployment frameworks, infrastructure, and tooling (Skilled) Optional Skills • Knowledge of information management, data strategy, and governance. • Commercial capability in value assurance, value estimation and realization, and end-to-end value mapping.