At a Glance
- Tasks: Analyse and optimise AI technologies to enhance shopping experiences.
- Company: Join Amazon's innovative Rufus Features Science team in London.
- Benefits: Competitive salary, diverse work culture, and opportunities for growth.
- Other info: Collaborate with a dynamic team of engineers and product managers.
- Why this job: Shape the future of AI-driven shopping with cutting-edge technology.
- Qualifications: Experience in machine learning, data analysis, and strong communication skills required.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry‑leading language technology powering Rufus, our AI‑driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey.
Key Responsibilities
- Analyze, model, and optimize AI technologies that will shape the future of shopping experiences.
- Measure and improve multimodal conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graphs tailored to customer needs.
- Handle Amazon‑scale use cases with significant impact on our customers' experiences.
- Collaborate with scientists, engineers, and product partners locally and abroad.
- Design experiments, analyze results, and launch new features, products and systems.
- Perform hands‑on analysis and modeling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys.
- Use 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 signals.
- Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights.
- Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact.
- Build predictive models and conduct deep‑dive analyses to identify opportunities for improving customer experience, conversion, and satisfaction.
- Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment.
- Establish automated processes for large‑scale data analysis, ETL pipelines, metric generation, and experimentation frameworks.
- Communicate results and insights to both technical and non‑technical audiences, including through presentations, written reports, and data visualizations.
About The Team
The Rufus Features Science team, based in London, works alongside approximately 150 engineers, designers and product managers, shaping the future of AI‑driven shopping experiences at Amazon. The team handles every aspect of Rufus AI, from enabling customers to set price alerts or letting Rufus act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance.
Basic Qualifications
- Experience with machine learning/statistical modeling and data analysis tools and techniques, and parameters that affect their performance.
- Experience in a ML or data scientist role with a large technology company.
- Experience with data scripting languages such as SQL, Python, R, or statistical/mathematical software.
- Experience effectively communicating complex concepts through written and verbal communication.
- Master’s degree or above in Math, Statistics, Computer Science, or related science field.
Preferred Qualifications
- Experience with AWS services including S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2.
- Experience in defining and creating benchmarks for assessing GenAI model performance.
- Experience working on multi‑team, cross‑disciplinary projects.
Equal Opportunity Statement
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. We are committed to diversity and inclusion. For accommodations during the application and hiring process, please refer to Amazon’s accommodations policy. For more information on privacy, consult the Amazon privacy notice.
Data Scientist II, RufusX Science UK in London employer: Amazon Science
At RufusX Science UK, we pride ourselves on fostering a dynamic and inclusive work environment where innovation thrives. As a Data Scientist II, you will have the opportunity to collaborate with a diverse team of experts in London, driving advancements in AI technology that enhance customer shopping experiences. We offer competitive benefits, continuous learning opportunities, and a culture that values creativity and teamwork, making us an exceptional employer for those seeking meaningful and impactful work.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist II, RufusX Science UK in London
✨Tip Number 1
Network like a pro! Reach out to current employees at RufusX Science or similar companies on LinkedIn. A friendly chat can give you insider info and might even lead to a referral, which is always a bonus!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your machine learning projects and data analyses. When you get the chance to chat with recruiters or during interviews, share specific examples of how you've tackled challenges in past roles.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for data scientists, especially those related to machine learning and analytics. Mock interviews with friends or using online platforms can help you nail your responses.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the team at RufusX Science.
We think you need these skills to ace Data Scientist II, RufusX Science UK in London
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for data science and machine learning shine through. We want to see that you’re not just qualified, but genuinely excited about the role and how you can contribute to shaping the future of shopping experiences.
Tailor Your Experience:Make sure to highlight your relevant experience with machine learning, data analysis, and any specific tools mentioned in the job description. We love seeing how your background aligns with what we’re looking for, so don’t hold back on showcasing your skills!
Communicate Clearly:Since effective communication is key, ensure your written application is clear and concise. Use straightforward language to explain complex concepts, as this will demonstrate your ability to communicate with both technical and non-technical audiences, which is super important for us.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s a straightforward process that gets you one step closer to joining our team!
How to prepare for a job interview at Amazon Science
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning and statistical modelling knowledge. Be ready to discuss specific algorithms you've used, how they performed, and any challenges you faced. This role is all about optimising AI technologies, so showing your expertise here will definitely impress.
✨Showcase Your Data Skills
Prepare to talk about your experience with data analysis tools like SQL, Python, or R. Have examples ready where you've handled large datasets or built predictive models. The more you can demonstrate your hands-on experience, the better!
✨Communicate Clearly
Since you'll need to explain complex concepts to both technical and non-technical audiences, practice articulating your thoughts clearly. Consider preparing a few key points or a mini-presentation on a project you've worked on that showcases your ability to communicate insights effectively.
✨Collaborate and Connect
This role involves working with various teams, so be prepared to discuss your collaboration experiences. Think of examples where you’ve worked cross-disciplinarily, and how you contributed to team success. Highlighting your teamwork skills will show you're a great fit for their collaborative environment.
