At a Glance
- Tasks: Design and deploy AI chatbots and data solutions that enhance product quality.
- Company: Global B2B information and professional services leader with a focus on innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team environment with significant visibility across the organisation.
- Why this job: Join a high-impact role and collaborate on cutting-edge AI projects.
- Qualifications: Strong Python and SQL skills, experience with chatbots and large datasets.
The predicted salary is between 70000 - 90000 £ per year.
Our client is a globally established B2B information and professional services business, operating across multiple high-value industry sectors. They have established data science and machine learning engineering teams already delivering in production, and are now expanding their AI capability significantly across the global organisation. This is a high-impact role with strong visibility across the organisation, working closely with product managers, engineers, and other data scientists to design and deploy AI, agentic and chatbot solutions that improve the quality of our products and automate complex workflows.
You’ll have the opportunity to work across the full lifecycle of data science: exploration, modelling, experimentation, and production deployment — while contributing to systems used by global AI Agents powered by LLMs and advanced RAG/Agentic architectures.
- LLM Chatbots that support user’s queries through automated search, content ranking and marketing campaigns evaluation.
- Smart Data Agents that interpret and summarise time series data.
- MCP Servers that allow internal and external services to securely interact with tools, APIs and databases.
You’ll have the autonomy to explore ideas, prototype new features, and collaborate with engineering teams to ship production-ready solutions.
- Build and deploy Chatbots, MCP Servers and Agentic models for our SaaS platforms.
- Collaborate with product and engineering teams to productionise models and pipelines.
- Contribute high-quality code to GitHub-based workflows and peer review processes.
- Validate model performance and maintain high standards for data and model accuracy.
- Communicate insights and technical solutions clearly to technical and non-technical stakeholders.
Core skills
- Strong Python and SQL skills – We want people who write clean code (using AI assistant coding is fine, but we want people that understand the language and can explain why they went with a certain approach).
- Experience building chatbots powered by RAG pipelines.
- Experience with LangGraph for agentic frameworks.
- Experience working with large, real-world datasets.
- Familiarity with cloud environments such as AWS, GCP, or Azure.
- Experience working in collaborative software environments using Git.
Candidate profile
- Exposure to recommendation systems or time-series forecasting.
- Solid understanding of ML models beyond “from sklearn import …”.
- A Masters or higher in a quantitative discipline (Statistics, Maths, Computer Science, Economics, etc.).
Nice to have
- Ability to work under tight deadlines and with minor supervision.