Applied Scientist (AI & Machine Learning)

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Applied Scientist (AI & Machine Learning)

City, London (Hybrid - 3 days per week)

£90,000 - 120,000, 15 - 20% bonus target

We're looking for an experienced Applied Scientist to help shape the future of AI within a leading global insurance organisation. This is an opportunity to solve complex business challenges using cutting-edge AI, machine learning, and large language models while setting technical standards for a high-performing data science team.

You'll play a hands-on leadership role, partnering with engineering and business stakeholders to design, build, and deploy AI solutions that deliver measurable business value.

What you'll do

• Lead the design and development of AI and machine learning solutions using LLMs, generative AI, and agentic AI.
• Solve complex business problems through advanced analytics, experimentation, and statistical modelling.
• Build production-ready AI solutions from concept through deployment and monitoring.
• Establish best practices for model evaluation, testing, validation, and responsible AI.
• Design and improve AI systems using techniques such as prompt engineering, retrieval augmented generation (RAG), and AI agents.
• Mentor data scientists and provide technical leadership through code reviews and coaching.
• Partner with engineering teams to deliver scalable, reliable AI solutions.
• Present technical concepts and recommendations to senior business stakeholders.

What we're looking for

• Extensive experience developing AI and machine learning solutions in production environments.
• Strong expertise in large language models, generative AI, RAG, prompt engineering, and agentic AI.
• Excellent Python programming skills and experience with modern AI and data science frameworks.
• Strong foundation in statistics, machine learning, and mathematical modelling.
• Experience designing evaluation frameworks for AI systems, including model performance and monitoring.
• Hands-on experience with Databricks, MLflow, Spark, or similar cloud-based data platforms.
• Knowledge of responsible AI, model governance, and explainability. xwwtmva
• Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.

Desirable

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