Senior Data Scientist – AI

About The Role

We are seeking a Senior Data Scientist to join our greenfield AI team in London. In this role, you won’t just build models in isolation; you will own the entire lifecycle—from training and fine-tuning models to deploying them into production‑grade systems that power our global enterprise planning platform.

This is a unique opportunity to bridge the gap between traditional predictive mathematics (such as high‑scale time‑series forecasting) and next‑generation Generative/Agentic AI. You will work across the full stack of our AI applications to build features that businesses rely on in real‑time.

Your Impact

• Advanced Modeling: Design, train, and implement advanced Machine Learning (ML) and Deep Learning (DL) models to solve complex business planning and forecasting problems.
• Predictive & Timeseries Forecasting: Develop robust, scalable time‑series models to enhance our platform’s predictive planning and scenario‑modeling capabilities.
• GenAI & LLM Integration: Implement and optimise Generative AI features, focusing on fine‑tuning open‑source LLMs (using LoRA, QLoRA, etc.) and building RAG pipelines.
• End-to-End Deployment (MLOps): Partner with our AI Engineers to transition your models from prototype into scalable, monitored, and reliable production microservices.
• Technical Mentorship: Actively contribute to code reviews, share technical best practices, and help mentor other data scientists and engineers on the team.

Your Skills

• Strong hands‑on professional experience in Artificial Intelligence, Machine Learning, or a highly quantitative field.
• Strong predictive modeling foundation: Deep expertise in traditional ML algorithms and time‑series forecasting.
• Hands‑on GenAI experience: Practical experience working with LLM APIs, prompt engineering, and fine‑tuning open‑source models.
• Production‑grade Python: High proficiency in Python and modern software practices (TDD, clean code, code review, CI/CD).
• MLOps Exposure: Experience with tools and frameworks for training, deploying, and monitoring models in production.

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