Expert Data Scientist

We are seeking an exceptional Expert Data Scientist to serve as a technical leader and architect of machine learning systems across the organisation.

This is the highest individual contributor tier within the field - a role for engineers and scientists who not only build world-class ML systems but define how they are built. You will shape architectural direction, establish engineering and scientific standards, and drive the delivery of complex, high-impact ML products that span the journey from research and experimentation through to solutions.

A core differentiator of this role is deep applied machine learning science: the ability to develop, validate, and deploy novel ML algorithms and scientific models as reliable, maintainable products - bridging the gap between innovative research and enterprise-scale deployment. You will influence multiple teams, mentor senior engineers, and drive step-change impact across business-critical, scientific, and R&D domains., * Provide technical leadership in the design and architecture of large-scale, production-grade ML systems and platforms across the organisation.

• Own end-to-end delivery of complex ML solutions - from scientific problem framing and algorithm design through to deployment, operationalisation, and product delivery.
• Apply advanced machine learning science to develop novel algorithms and models, ensuring they are rigorously validated and deployed as scalable, reliable, production-grade products.
• Bridge the gap between scientific research and enterprise deployment - taking ML innovations from experimentation through to productised, maintainable solutions that deliver measurable value.
• Drive engineering excellence across ML systems, including CI/CD, testing, observability, reliability, and MLOps guidelines.
• Define technical standards, patterns, and protocols for ML engineering and applied ML science across teams.
• Lead complex, multi-team technical initiatives and influence organisational direction through technical authority.
• Evaluate and integrate emerging approaches - including generative AI, Agentic AI, advanced optimisation, and scientific computing - into scalable solutions.
• Supply to and shape internal ML platforms, reusable frameworks, and shared scientific computing capabilities.
• Mentor senior engineers and data scientists, raising the technical bar across the subject area.
• Partner with business and scientific customers to shape ML strategy and identify high-value opportunities.
• Present technical strategies, architectural decisions, and outcomes to senior leadership.

• MSc, PhD degree or equivalent experience in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering, or related subject area).
• Hands-on experience designing, prototyping, productionizing, and scaling complex ML systems in production environments.
• Deep and demonstrable expertise in machine learning algorithms, statistical modelling, optimisation techniques, and scientific computing - with a consistent record of applying these to deliver production-grade products.
• Strong software engineering and system design expertise, including distributed systems, scalable architectures, and API design.
• Advanced programming experience in languages such as Python, Go, Java, or C++.
• Advanced SQL knowledge.
• Strong experience with MLOps, production ML systems, model lifecycle management, and monitoring.
• Experience working with large-scale data systems and distributed computing frameworks (e.g. Spark, Hadoop).
• Knowledge of experimental design, scientific methodology, and analysis.
• Strong partner management and confirmed ability to influence large organisations without direct authority.
• Demonstrated ability to lead through technical excellence and deliver high-impact, organisation-wide outcomes.
• Continuous learning and improvement approach., * Deep experience in applied machine learning science - including developing novel algorithms and translating research into deployable, production-grade ML products.
• Experience applying AI/ML to scientific, engineering, or R&D workflows - encompassing experimentation, simulation, optimisation, physics-informed modelling, and autonomous scientific workflows.
• Strong experience with generative AI (LLMs, RAG, multimodal systems) and their deployment in production.
• Experience designing or deploying Agentic AI systems - including autonomous agents, tool use, multi-agent orchestration, reasoning workflows, and agent-driven scientific discovery.
• Consistent record of innovation through publications in peer-reviewed venues, invention disclosures (IDFs), patents, or open-source contributions in machine learning or AI.
• Experience building ML platforms, reusable scientific computing frameworks, or internal tooling that accelerates delivery across teams.
• Familiarity with model interpretability, uncertainty quantification, and advanced experimental frameworks.
• No prior experience in the energy industry required., Agility core practices, Agility core practices, API and platform design, Cloud Platforms, Collaboration, Communication, Configuration management and release, Continuous deployment and release, Creating a high performing team, Database Design, Digital Project Management, Documentation and knowledge sharing, Emerging technology monitoring, Facilitation, Information Security, Mentoring, Metrics definition and instrumentation, NoSql data modelling, Problem Solving, Relational Data Modeling, Risk Management, Scripting, Secure development, Service operations and resiliency, Software Design and Development {+ 7 more}

• Competitive compensation and benefits package.
• Opportunity to lead and shape the future of ML and AI at one of the world’s largest energy companies.
• A culture that values scientific difficulty, engineering excellence, and continuous learning.
• Hybrid working arrangements and a commitment to work-life balance.
• Career development pathways in a world-class technology organisation.

Please remember that the business title for this role, which will be reflected in the employment contract, is Staff Machine Learning Engineer.

Please note that roles based out of SJS or Sunbury will move to Timber Square, Southwark, from Q4 2027, There are many aspects of our employees’ lives that are meaningful, so we offer benefits to enable your work to fit with your life. These benefits can include flexible working options, a generous paid parental leave policy, excellent retirement benefits, among others!