At a Glance
- Tasks: Develop scalable ML models and collaborate on AI solutions for Prime Video.
- Company: Join Amazon Science in London, a leader in tech innovation.
- Benefits: Competitive salary, health benefits, and opportunities for global collaboration.
- Other info: Dynamic research environment with excellent networking opportunities.
- Why this job: Make a real impact on user experience for billions of customers.
- Qualifications: Experience in machine learning and strong collaboration skills.
Amazon Science in London is seeking an Applied Scientist to advance Prime Video’s observability and user experience. You will develop scalable ML models and collaborate with cross-functional teams across the UK, India, and the US to deploy impactful AI solutions.
The role involves hands-on research, experimentation, and close collaboration with engineers to productionize successful models that impact billions of customers. A strong publication/networking background is valued.
#J-18808-LjbffrApplied Scientist, Observability & Generative AI employer: Amazon Science
Amazon Science in Edinburgh is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. Employees benefit from opportunities for professional growth and development, while contributing to impactful projects that enhance recruitment technologies. With a focus on cutting-edge AI solutions, this role allows you to play a pivotal part in shaping the future of hiring at one of the world's leading companies.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist, Observability & Generative AI
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Amazon Science!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Applied Scientist, Observability & Generative AI at Amazon Science.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Amazon Science.
✨Apply Directly through Our Website
When you find a suitable opening like Applied Scientist, Observability & Generative AI at Amazon Science, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Applied Scientist, Observability & Generative AI
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Amazon Science, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Amazon Science. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Amazon Science
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Amazon Science!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
