Applied Scientist, Ads & Recommendation ML in London

Applied Scientist, Ads & Recommendation ML in London

London Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Amazon Science

At a Glance

  • Tasks: Design and implement deep learning models to enhance ad matching.
  • Company: Join Amazon Science in Greater London, a leader in innovation.
  • Benefits: Competitive salary, health benefits, and opportunities for professional growth.
  • Other info: Fast-paced environment with collaboration and creativity at its core.
  • Why this job: Innovate in advertising strategies and make a real impact.
  • Qualifications: PhD or Master’s in machine learning with programming experience.

The predicted salary is between 60000 - 80000 £ per year.

Amazon Science in Greater London is looking for a skilled professional to design and implement deep learning models that enhance matching of ads based on various criteria. You will collaborate closely with engineers and utilize both quantitative analysis and creativity to develop solutions in the fast-paced world of advertising.

The ideal candidate has a PhD or Master’s with relevant experience in machine learning, programming, and deep learning architectures. This position offers an opportunity to innovate and contribute to advertising strategies.

Applied Scientist, Ads & Recommendation ML in London employer: Amazon Science

Amazon Science in Greater London is an exceptional employer that fosters a culture of innovation and collaboration, providing employees with the opportunity to work on cutting-edge machine learning projects that directly impact advertising strategies. With a strong emphasis on professional growth, employees benefit from continuous learning opportunities and the chance to work alongside industry experts in a dynamic environment. The vibrant location in Greater London further enhances the experience, offering a rich blend of cultural and professional opportunities.

Amazon Science

Contact Details:

Amazon Science Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Applied Scientist, Ads & Recommendation ML in London

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, Ads & Recommendation ML at Amazon Science.

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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, Ads & Recommendation ML 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, Ads & Recommendation ML in London

Deep Learning
Machine Learning
Programming
Quantitative Analysis
Creativity
Collaboration
Advertising Strategies

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.