At a Glance
- Tasks: Develop and prototype machine learning algorithms for Prime Video recommendations.
- Company: Join Amazon Science, a leader in innovative technology.
- Benefits: Competitive salary, great perks, and a focus on professional growth.
- Other info: Collaborate with engineering teams and leverage vast data analytics.
- Why this job: Make an impact with cutting-edge ML tech in a dynamic environment.
- Qualifications: PhD in relevant fields and strong programming skills required.
The predicted salary is between 60000 - 80000 € per year.
Amazon Science is seeking a Machine Learning Scientist in Greater London. The role involves developing and prototyping machine learning algorithms for Prime Video recommendations, collaborating with engineering teams, and leveraging vast data analytics.
Applicants should possess a PhD in relevant fields, with programming expertise and experience in applied research. This position offers an innovative working environment focused on delivering value to customers and leveraging cutting-edge machine learning technologies.
Senior Applied Scientist, Insights - ML for Recommendations employer: Amazon Science
Amazon Science is an exceptional employer, offering a dynamic and innovative work culture in Greater London that fosters collaboration and creativity. Employees benefit from access to cutting-edge machine learning technologies, ample opportunities for professional growth, and a commitment to delivering impactful solutions for customers. Join us to be part of a forward-thinking team that values your expertise and encourages continuous learning.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Applied Scientist, Insights - ML for Recommendations
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Amazon Science on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your machine learning projects, especially those related to recommendations. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on algorithms and data structures. We can even do mock interviews with friends to build confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can tailor our CVs and cover letters to match the job description perfectly.
We think you need these skills to ace Senior Applied Scientist, Insights - ML for Recommendations
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your relevant experience in machine learning and applied research. We want to see how your skills align with the role, so don’t be shy about showcasing your programming expertise and any projects that relate to recommendations.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team at Amazon Science. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Projects:If you've worked on any interesting machine learning projects, make sure to mention them! We’re keen to see how you’ve applied your knowledge in real-world scenarios, especially if they relate to recommendations or data analytics.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our innovative team!
How to prepare for a job interview at Amazon Science
✨Know Your Algorithms
Brush up on the latest machine learning algorithms, especially those relevant to recommendations. Be ready to discuss how you've applied these in your past work and how they can be adapted for Prime Video.
✨Showcase Your Collaboration Skills
Since this role involves working closely with engineering teams, prepare examples of successful collaborations. Highlight how you’ve effectively communicated complex ideas to non-technical team members.
✨Demonstrate Data Savvy
Familiarise yourself with data analytics tools and techniques. Be prepared to discuss how you’ve leveraged data in your previous projects to drive insights and improve outcomes.
✨Prepare for Technical Questions
Expect technical questions that test your programming skills and understanding of machine learning concepts. Practice coding problems and be ready to explain your thought process clearly.
