Applied Scientist, Prime Video Commerce Insights

Amazon; Greater London; Hybrid; GBP 110,000 - 150,000; Full time

Job summary

Amazon Development Centre (London) Limited is hiring an Applied Scientist for Prime Video Commerce Insights in London. You will lead ML research and deliver customer-facing models that impact how shoppers discover and buy content, across devices and markets.

You will collaborate with engineers and product teams to deploy models at scale, run experiments, and shape the science agenda. The role demands technical depth, strategic thinking, and the ability to translate business questions into

Qualifications

• Proficient in Java, C++, or Python with production ML experience.
• Experience building ML models for business use.
• Strong background in algorithms and data structures.

Responsibilities

• Research, design, and implement ML approaches that personalise across touchpoints.
• Collaborate with engineers to deploy results into large-scale systems with low latency.
• Design and run rigorous experiments to prove efficacy and business value.
• Define science roadmap and research agenda aligned with priorities.
• Provide ML thought leadership to technical and business leaders.
• Work with product managers to deliver ML-backed solutions.
• Share results through rigorous, relevant documentation.

Skills

Java

C++

Python

Machine learning

Algorithms

Data mining

Distributed computing

Education

Bachelor's degree in CS/CE/ML

Master's degree in relevant field

Job description

Applied Scientist, Prime Video Commerce Insights

Job ID: 10579750 | Amazon Development Centre (London) Limited

Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies — all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business — available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. Prime Video Commerce's mission is to present the right offer to the right customer at the right time — across subscriptions, channels, and transactional video, in every market and on every device. Our science team replaces static business rules with ML-driven decisions that personalise the entire commerce journey, from discovery through checkout and beyond. We operate at scale across hundreds of millions of customers, and we are expanding into new frontiers — combining the latest advances in agentic and generative AI, behavioural simulation, and causal inference to understand the impact of our decisions before they reach customers. We are looking for an Applied Scientist to join the Prime Video Commerce Insights team in London. You will develop and deploy customer-facing models, understand customer behaviour at scale, and explore emerging techniques that help us make better decisions faster. This is a delivery focused role within a high-visibility multidisciplinary group of engineers and scientists, focused on improving the customer experience for Prime Video.

Key job responsibilities

• Research, design, and implement machine learning approaches (e.g. reinforcement learning and recommendation systems) that personalise across different customer touch points.
• Collaborate with engineers to deploy and integrate successful experiment results into large-scale, complex Amazon production systems with low latency.
• Design and execute rigorous experiments to demonstrate the technical efficacy and business value of your methods.
• Act as a subject-matter expert and help define the science roadmap and research agenda in line with organisational priorities and production constraints.
• Provide machine learning thought leadership to technical and business leaders, thinking strategically about business, product, and technical challenges.
• Work with technical product managers to work backwards from what matters to customers and deliver ML-backed solutions.
• Share results with the team and wider scientific community through documents that are both statistically rigorous and compellingly relevant.

A day in the life

You will be a research leader and innovator within the Commerce Insights organisation. You will collaborate with talented engineers and senior leaders to solve problems that are uniquely challenging at Amazon's scale: personalising commerce decisions across multiple business lines, balancing competing objectives, and positively impacting hundreds of millions of customers worldwide. The problems here are technically deep — combining large-scale ML, causal reasoning, and behavioural modelling in a domain where every decision carries real revenue and customer-experience consequences. Your research will ship to production and move metrics that matter.

About the team

You will join a team of engineers and applied scientists with a proven track record of solving highly complex, ambiguous problems — work that has produced patents and publications at top-tier conferences. The team has direct visibility to senior Prime Video leadership and collaborates broadly across Commerce, Content, and Platform teams to shape how customers discover, subscribe to, and engage with video content. This is a team that operates at the intersection of rigorous research and real-world impact, where your ideas move from whiteboard to production for hundreds of millions of customers.

Basic Qualifications

• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience in building machine learning models for business application
• Professional non-internship experience in a relevant field (CS, CE, ML)

Preferred Qualifications

• Experience implementing algorithms using both toolkits and self-developed code
• Have publications at top-tier peer-reviewed conferences or journals
• Master's degree in a relevant field, or equivalent qualification/experience

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.