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 professional 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.
The predicted salary is between 55000 - 70000 £ 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 employer: Amazon Science
At RufusX Science UK, we pride ourselves on fostering a dynamic and inclusive work culture that encourages innovation and collaboration among our talented team of data scientists and engineers. Located in the vibrant city of London, we offer exceptional employee growth opportunities through hands-on projects and cross-disciplinary teamwork, all while contributing to cutting-edge AI technology that enhances customer shopping experiences. Join us to be part of a forward-thinking company that values diversity and empowers its employees to make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist II, RufusX Science UK
✨Tip Number 1
Network like a pro! Reach out to current employees at RufusX Science on LinkedIn or other platforms. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your machine learning concepts and data analysis techniques. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your experience and skills.
✨Tip Number 3
Showcase your projects! If you've worked on any relevant data science projects, make sure to highlight them during your interview. Bring along examples of your work, especially those that demonstrate your ability to handle large datasets and create impactful models.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. 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
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 those details!
Communicate Clearly:Since you'll be working with both technical and non-technical teams, it's crucial to demonstrate your ability to communicate complex concepts effectively. Use clear language and examples in your written application to show us you can bridge that gap.
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 gives you a chance to explore more about our team and culture!
How to prepare for a job interview at Amazon Science
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning and statistical modelling skills. Be ready to discuss specific projects you've worked on, especially those involving large datasets or AI technologies. This will show that you not only understand the theory but can also apply it in real-world scenarios.
✨Prepare for Technical Questions
Expect technical questions related to data analysis tools like SQL, Python, or R. Practise coding challenges or case studies that involve designing experiments or analysing A/B test results. This will help you demonstrate your problem-solving skills and technical expertise.
✨Showcase Your Communication Skills
Since you'll need to communicate complex concepts to both technical and non-technical audiences, prepare examples of how you've done this in the past. Think about how you can explain your findings clearly and concisely, perhaps through a mock presentation or a written report.
✨Understand the Company and Its Products
Research RufusX Science and its AI-driven shopping assistant. Familiarise yourself with their technology and think about how your skills can contribute to enhancing customer experiences. Showing genuine interest in the company will set you apart from other candidates.
