Data Scientist, Emeia Sales

Apple Apple · Big Tech · London, United Kingdom +1 · Sales and Business Development

This role focuses on developing and deploying AI-powered applications, specifically agentic systems, for sales use cases. The Data Scientist will research, test, and implement these solutions, working with various stakeholders to drive AI adoption and educate non-technical teams. The role involves hands-on work with LLMs, agent frameworks, and prompt engineering, with a good understanding of RAG and vector databases.

What you'd actually do

  1. Providing support in researching, testing & applying the latest agentic frameworks to build truly agentic applications for sales use cases
  2. Provide training, testing and deployment of machine learning models to be integrated into AI enabled applications and automation workflows
  3. Experiment & Evaluate the latest AI technologies including LLMs and agent-based systems
  4. Act as a subject matter enthusiast on AI and machine learning topics within the sales organisation
  5. Share knowledge to help up-skill non-technical teams members on fundamentals of AI and machine learning using practical examples

Skills

Required

  • SQL
  • Python
  • AI Coding tools : Claude Code, Codex
  • Deep understanding of machine learning fundamentals
  • Deep understanding of how LLMs and agentic systems work and build agentic AI apps
  • Strong Curiosity with AI and a an ongoing passion for learning
  • Strong Interpersonal Skills: Ability to communicate clearly to both technical and non-technical stakeholders/teams
  • Exposure to modern AI frameworks or orchestration tools (LangGraph etc)
  • Deep experience with LLM APIs and prompt engineering
  • Familiarity with cloud platforms e.g. AWS, Azure, GCP
  • Good understanding of APIs, vector databases or RAG architectures
  • Experience working with commercial, operational & sales data

Nice to have

  • Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Engineering or a related technical field, or equivalent experience.

What the JD emphasized

  • Deep understanding of how LLMs and agentic systems work and build agentic AI apps
  • Deep experience with LLM APIs and prompt engineering
  • Exposure to modern AI frameworks or orchestration tools (LangGraph etc)
  • Good understanding of APIs, vector databases or RAG architectures

Other signals

  • Develop intelligent, agentic, and machine learning-powered applications
  • Research, test, and deploy modern AI solutions
  • Build truly agentic applications for sales use cases
  • Experiment & Evaluate the latest AI technologies including LLMs and agent-based systems
  • Deep understanding of how LLMs and agentic systems work and build agentic AI apps