Senior Data Scientist - Personalisation & Generative AI

Data Science Festival; Greater London; Hybrid; GBP 80,000 - 85,000; Full time

Job summary

Data Idols is recruiting a Senior Data Scientist to develop next-generation recommendation engines, conversational AI experiences, and personalization models for a large-scale digital platform. You will design, build and deploy production-grade ML models powering highly personalised customer experiences, including recommendation algorithms, retrieval systems and LLM-powered conversational AI.

You will work closely with Product Managers, Engineers and MLOps to move ideas from experimentation into

Qualifications

• Strong commercial experience with Python.
• Excellent understanding of machine learning, statistical modelling and experimental design.
• Experience developing and deploying end-to-end machine learning products into production.
• Knowledge of recommender systems, personalisation, retrieval or ranking techniques is highly desirable.
• Experience working with LLMs, Generative AI or conversational AI products would be advantageous.

Responsibilities

• Design, build and deploy production-grade ML models powering personalised customer experiences.
• Work on recommendation algorithms and retrieval systems, up to LLM-powered conversational AI.
• Collaborate with Product Managers, Engineers and MLOps to move ideas from experiments to production.

Skills

Python

Machine learning

Experiment design

Production deployment

Recommender systems

Retrieval techniques

LLMs

Generative AI

Job description

Data Idols is recruiting a Senior Data Scientist to develop next-generation recommendation engines, conversational AI experiences, and personalization models for a large-scale digital platform. You will design, build and deploy production-grade ML models powering highly personalised customer experiences, including recommendation algorithms, retrieval systems and LLM-powered conversational AI.

You will work closely with Product Managers, Engineers and MLOps to move ideas from experimentation into