About this role
Salary: £60,000 - 110,000 per year
Requirements: Experience with machine learning/statistical modeling, data analysis tools and techniques, and the parameters that affect their performanceExperience in a ML or data scientist role with a large technology companyExperience with data scripting languages such as SQL, Python, or R, or statistical/mathematical software such as R, SAS, or MatlabExperience effectively communicating complex concepts through written and verbal communicationA masters degree or above in Math, Statistics, Computer Science, or a related science fieldExperience with AWS services including S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2Experience in defining and creating benchmarks for assessing GenAI model performanceExperience working on multi-team, cross-disciplinary projects Responsibilities: Perform hands-on analysis and modeling of large multimodal datasets to develop insights into how to best help customers throughout their shopping journeysUse statistical methods, machine learning, and data mining techniques to create scalable solutions for measuring and optimizing shopping assistant systems based on structured and unstructured contextual signalsDesign and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insightsDevelop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impactBuild predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience, conversion, and satisfactionCollaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deploymentEstablish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworksCommunicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations Technologies: AIAWSLambdaRedshiftEC2ETLMachine LearningMatlabPythonSASSQLCloudSupportSecurityWeb More:
We are building industry-leading language technology powering Rufus, our AI-driven search and shopping assistant, to help customers with their shopping tasks at every step of their journey. Our mission in conversational shopping is to make it easy for customers to find and discover the best products by helping with product research, comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We leverage advanced analytics, Natural Language Processing, Machine Learning, A/B testing, causal inference, and data-driven insights to continuously improve our systems. Our Rufus Features Science team is based in London and works alongside around 150 engineers, designers, and product managers shaping the future of AI-driven shopping experiences. The team works across the Rufus AI experience, including agentic features, multimodal query understanding, and answers that combine text, image, audio, and video, as well as deep research reports that provide detailed, personalised shopping guidance.
last updated 40 week of 2026