Expert Data Scientist

Overview

In this role you will lead the design and delivery of large-scale ML systems, spanning research to production. You’ll set architectural direction, raise engineering standards, and drive high-impact ML products across teams. You’ll turn scientific advances into reliable, scalable solutions and mentor other engineers, shaping bp’s ML platform strategy and execution. This role combines deep ML expertise with systems engineering to deliver enterprise-grade outcomes at scale.

Pay / Benefits

• Competitive compensation and benefits package
• Hybrid working arrangements
• Career development pathways
• Diversity and inclusion
• Parental leave policy
• Excellent retirement benefits

Responsibilities

• Provide technical leadership in the design and architecture of large-scale, production-grade ML systems across the organization
• Own end-to-end delivery of complex ML solutions—from framing and algorithm design to deployment and product delivery
• Develop novel ML algorithms and models with rigorous validation for scalable, production-grade deployment
• Bridge research and deployment by productising experimental innovations
• Drive ML engineering excellence including CI/CD, testing, observability, reliability, and MLOps guidelines
• Define technical standards, patterns, and protocols for ML engineering across teams
• Lead multi-team technical initiatives and influence organizational direction
• Evaluate and integrate emerging approaches (generative AI, Agentic AI, advanced optimisation) into scalable solutions
• Contribute to internal ML platforms, reusable frameworks, and shared computing capabilities
• Mentor senior engineers and data scientists to raise technical standards
• Partner with business and scientific customers to shape ML strategy and opportunities
• Present technical strategies and outcomes to senior leadership

Key requirements

• MSc, PhD or equivalent in a quantitative field
• Hands-on experience designing, prototyping, productionising, and scaling ML systems
• Deep expertise in ML algorithms, modelling, optimization, and scientific computing
• Strong software engineering and system design skills (distributed systems, scalable architectures, API design)
• Advanced programming in Python, Go, Java, or C++
• Advanced SQL knowledge
• Experience with MLOps, production ML systems, and model lifecycle management
• Experience with large-scale data systems and distributed frameworks (Spark, Hadoop)
• Knowledge of experimental design and scientific methodology
• Strong partner management and ability to influence without authority
• Proven ability to lead through technical excellence and deliver broad outcomes
• Continuous learning mindset

• Strong communication and presentation to senior leadership
• Mentoring and coaching of engineers and data scientists
• Cross-functional collaboration
• Python
• Go
• Java

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