Senior Production ML Scientist

Remote Worker LTD.; Sunbury-on-Thames; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Competitive compensation

Global scale ML problems

Culture of scientific rigour and learn

Hybrid working arrangements

Career development pathways

Job summary

bp is seeking a Senior Data Scientist who combines deep machine learning expertise with strong software engineering to design, build, and deploy production-grade ML systems.

This role goes beyond traditional ML engineering, applying ML as a core field to develop novel algorithms and models that are deployed as scalable products across NLP, optimisation, simulation, or generative AI. You will work in a cross-disciplinary team of data scientists, software engineers and data engineers.

Qualifications

• MSc, PhD degree or equivalent experience in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering, or related discipline).
• Hands-on experience designing, prototyping, productionising, maintaining, and scaling ML/data science products in complex environments.
• Strong and demonstrable expertise in machine learning algorithms, statistical modelling, and optimisation techniques - with a track record of applying these to build production-grade solutions.
• Applied knowledge of data science and ML tools across all stages of the data and model lifecycle.
• Thorough understanding of the mathematical foundations of statistics, machine learning, and scientific computing.
• Strong programming experience in one or more object-oriented languages (e.g. Python, Go, Java, C++).
• Advanced SQL knowledge.
• Experience with modern ML engineering practices including MLOps, model lifecycle management, CI/CD, and monitoring.
• Knowledge of experimental design, analysis, and scientific methodology.
• Customer-centric and pragmatic mentality with a focus on value delivery and swift execution, while maintaining rigour and attention to detail.
• Strong partner management and ability to influence across teams and organisations.
• Continuous learning and improvement mentality.

Responsibilities

• Design, build, and maintain scalable, production-grade machine learning systems and pipelines using modern engineering practices (CI/CD, testing, monitoring, observability).
• Apply machine learning science to develop novel algorithms and models that are deployed as reliable, scalable products - not limited to experimentation but extending through to production delivery and operational use.
• Build impactful ML products demonstrating statistical modelling, deep learning, and AI techniques across operational, scientific, and R&D domains.
• Translate complex scientific and business problems into well-scoped ML solutions, delivering actionable insights and deployable capabilities.
• Architect and optimise ML systems for performance, scalability, and reliability in production environments.
• Collaborate closely with data scientists, data engineers, software engineers, and domain authorities as part of cross-disciplinary teams.
• Adhere to and advocate for engineering and data science guidelines (technical design, design reviews, unit testing, monitoring & alerting, code reviews, documentation).
• Present technical results, trade-offs, and product outcomes to peers and senior partners.
• Actively supply to improving developer velocity, engineering standards, and shared tooling.
• Mentor junior team members and chip in to the technical growth of the wider team.

Skills

Python

Go

Java

C++

SQL

MLOps

CI/CD

Unit testing

Monitoring

Education

MSc/PhD in CS or related

Tools

Cloud Platforms

CI/CD tools

NoSQL databases

Spark

Hadoop

Job description

bp is seeking a Senior Data Scientist who combines deep machine learning expertise with strong software engineering to design, build, and deploy production-grade ML systems.

This role goes beyond traditional ML engineering, applying ML as a core field to develop novel algorithms and models that are deployed as scalable products across NLP, optimisation, simulation, or generative AI. You will work in a cross-disciplinary team of data scientists, software engineers and data engineers.